Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

iOS Developer SE Gurugram, Haryana, India– Engineering /Full-Time/ Work from Office At OLX India, we work together to build a more sustainable world through trade. We make it safe, smart, and convenient to buy and sell cars, find housing, get jobs, buy and sell household goods, and more. We are looking for an iOS Engineer who is a talented super ninja programmer and is interested in being part of a platform that handles millions of requests per day. Continuous integration, auto-scaled rolling releases, event-driven microservice architectures are all part of the daily gig. What You will be doing : ● You will work closely with other teams from the early stages of design all the way through identifying and resolving production issues. ● You will support a wide range of products focusing on automation, availability and performance and above all reliability as well as supporting other engineers and business intelligence leading up to, during and after each sprint. ● You will live true to our ambitions of building an industry leading platform which is relentlessly focused on innovation. ● Write architecturally sound and maintainable code following best programming practices. ● Work in a mentoring capacity within a peer-programming environment and provide guidance on tasks, irrespective of complexity or scale. ● Handle the entire software development life cycle, end to end. ● Unit-test code for robustness, including edge cases, usability and reliability. ● Working with our testing team to ensure 100% test coverage. ● Discovering and implementing the newest technologies. Who we are looking for: ● 2+ years experience of iOS development and Swift. ● Strong command on Swift, UIKit, CoreDataDeep knowledge of latest mobile architectures [MVC, MVVM, etc], design patterns, SOLIDA good understanding of RESTful applications ● Experience working in cross-functional teams (ability to coordinate with product, design, BE devs and QA) ● Have published at least one iOS App to the market ● You can talk all day about GCD, multi threading, process and memory optimisations ● The ability to create beautiful, elegant and pixel perfect user interfaces ● Understanding of Agile methodologies and SCRUM ● You understand git commands and have worked with Github, Gitlab or any git repository platform ● Ability to prioritise tasks and quickly adjust in a rapidly changing environment. ● Working with our testing team to ensure 100% test coverage [UTs, FTs, etc]iOS platform testing strategies (Unit Tests, Snapshot Tests, etc) is a plus ● Reactive programming (RxSwift) is a plusCI/CD (Bitrise, Gitlab, Fastlane) is a plus ● Experience working with BFF [backend-for-frontend] layer is a plus What we'll give you An opportunity to shape a largely unorganised industry and help millions of car buyers and sellers transact with trust and efficiency. Passionate team and leadership colleagues who will share the dream and drive to deliver the most trusted, convenient and innovative car buying and selling experiences. Opportunities to speed up your learning and development across your role relevant areas At OLX, we are committed to creating a diverse, inclusive, and authentic workplace. We strongly encourage people of all races, ethnicities, disabilities, ages, gender identities or expressions, sexual orientations, religions, backgrounds, and experiences to apply. We embrace diversity and welcome applicants from all backgrounds. If you are as excited as us about this position and our company, we hope you join us! "Our Success is fueled by diverse perspectives and talents" Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

We are hiring a Software Tester (QA) on an urgent basis, who can join our team and work very closely with our developers. Experience: 6 Months to 2 years Skills Required: Knowledge of Manual & Auto functional testing, Web applications testing, SDLC & SQL Strong analytical and problem-solving skills Familiarity with various testing tools and techniques Must collaborate with developers to resolve issues Good communication and collaboration skills Qualification: Graduate (BCA, BE/ B.Tech In Computer Or IT), MCA & Diploma In Computer Or IT Location: Surat (Gujarat) Interested candidates are requested to send their updated resumes. Job Type: Full-time Pay: ₹10,000.00 - ₹20,000.00 per month Schedule: Morning shift Work Location: In person Speak with the employer +91 7802852282

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Responsibilities Implementation of Core-PAS CyberArk components (EPV, DR EPV, HA EPV, PVWA, PSM, PSMP, CPM). Implementation of Privileged Threat Analytics (PTA) Implementation of Advanced Modules (AAM – CP, AAM – CCP, Alero, HTML 5) Development of Connection components using Auto-IT for Web applications & thick clients Knowledge about PAM Access Reviews Knowledge about Identity modules (Eg: Sailpoint, ISIM) Knowledge about Access Modules (Eg: Azure SSO, ISAM) Knowledge about Active Directories (Microsoft AD, Azure AD) Integration of SIEM, SNMP, SMTP, SAML, LDAPS with CyberArk Development of CPM Plugins for SSH & Web based applications. Certification – Defender/Sentry (Mandatory), CDE (Optional) Preparation of Architecture designs for all modules of CyberArk Creation & review of High level project plan Provide consulting advise to customer/stakeholders during technical discussions. Creation of Project Documentation (HLD, DTD, SoP, KEDB, Breakglass, etc.,) Assist colleagues from Support & Project team with technical queries Knowledge on CyberArk REST API’s Atleast 1 Programming Language at L2 level (Eg: Powershell, Python, etc.,) Able to assist Develop & tester with Automation initiates Able to create Discovery rules Run DNA Scans Hands-on with Device types – Windows, *Nix, Network, Database, SAP, Web applications, Tier 0&1 accounts, Domain Controllers Understanding of Azure PIM Knowledge about one more PAM solution is a added advantage Assist with new SOW/Contract Creation & prepare effort estimation for new initiates Prepare roadmap for the customer based on the vision Knowledge about Power BI reporting Knowledge about PAS Reporter, Telemetry, Export Vault Data Show more Show less