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

Job Title : Data Testing Engineer Exp : 8+ years Location : Hyderabad and Gurgaon (Hybrid) Notice Period : Immediate to 15 days Job Description : Develop, maintain, and execute test cases to validate the accuracy, completeness, and consistency of data across different layers of the data warehouse. ● Test ETL processes to ensure that data is correctly extracted, transformed, and loaded from source to target systems while adhering to business rules ● Perform source-to-target data validation to ensure data integrity and identify any discrepancies or data quality issues. ● Develop automated data validation scripts using SQL, Python, or testing frameworks to streamline and scale testing efforts. ● Conduct testing in cloud-based data platforms (e.g., AWS Redshift, Google BigQuery, Snowflake), ensuring performance and scalability. ● Familiarity with ETL testing tools and frameworks (e.g., Informatica, Talend, dbt). ● Experience with scripting languages to automate data testing. ● Familiarity with data visualization tools like Tableau, Power BI, or Looker Show more Show less

Job Summary We are seeking a highly skilled and detail-oriented Senior SQL Data Analyst to join our data-driven team. This role will be responsible for leveraging advanced SQL skills to extract, analyze, and interpret complex datasets, delivering actionable insights to support business decisions. You will work closely with cross-functional teams to identify trends, solve problems, and drive data-informed strategies across the organization. Key Responsibilities Develop, write, and optimize advanced SQL queries to retrieve and analyze data from multiple sources. Design and maintain complex data models, dashboards, and reports. Collaborate with stakeholders to understand business needs and translate them into analytical requirements. Conduct deep-dive analysis to identify key business trends and opportunities for growth or improvement. Ensure data integrity and accuracy across systems and reporting tools. Automate recurring reports and develop scalable data pipelines. Present findings in a clear, compelling way to both technical and non-technical audiences. Qualifications Required: Bachelor's degree in Computer Science, Information Systems, Mathematics, Statistics, or related field. 5+ years of experience in data analysis or a similar role with a strong focus on SQL. Expert proficiency in SQL (window functions, joins, CTEs, indexing, etc.). Strong understanding of data warehousing concepts and relational database systems (e.g., PostgreSQL, SQL Server, Snowflake, Redshift). Experience with BI tools like Tableau, Power BI, or Looker. Excellent analytical, problem-solving, and communication skills. Preferred Experience with scripting languages (Python, R) for data manipulation. Familiarity with cloud data platforms (AWS, Azure). Knowledge of ETL tools and best practices. Previous experience in a fast-paced, agile environment. Show more Show less

You will lead the development of predictive machine learning models for Revenue Cycle Management analytics, along the lines of: 1 Payer Propensity Modeling - predicting payer behavior and reimbursement likelihood 2 Claim Denials Prediction - identifying high-risk claims before submission 3 Payment Amount Prediction - forecasting expected reimbursement amounts 4 Cash Flow Forecasting - predicting revenue timing and patterns 5 Patient-Related Models - enhancing patient financial experience and outcomes 6 Claim Processing Time Prediction - optimizing workflow and resource allocation Additionally, we will work on emerging areas and integration opportunities—for example, denial prediction + appeal success probability or prior authorization prediction + approval likelihood models. You will reimagine how providers, patients, and payors interact within the healthcare ecosystem through intelligent automation and predictive insights, ensuring that providers can focus on delivering the highest quality patient care. VHT Technical Environment 1 Cloud Platform: AWS (SageMaker, S3, Redshift, EC2) 2 Development Tools: Jupyter Notebooks, Git, Docker 3 Programming: Python, SQL, R (optional) 4 ML/AI Stack: Scikit-learn, TensorFlow/PyTorch, MLflow, Airflow 5 Data Processing: Spark, Pandas, NumPy 6 Visualization: Matplotlib, Seaborn, Plotly, Tableau Show more Show less

Job Summary: We are seeking a highly skilled Lead Data Engineer/Associate Architect to lead the design, implementation, and optimization of scalable data architectures. The ideal candidate will have a deep understanding of data modeling, ETL processes, cloud data solutions, and big data technologies. You will work closely with cross-functional teams to build robust, high-performance data pipelines and infrastructure to enable data-driven decision-making. Experience: 7 - 12 years Work Location: Hyderabad (Hybrid) / Remote Mandatory skills: AWS, Python, SQL, Airflow, DBT Must have done 1 or 2 projects in Clinical Domain/Clinical Industry. Responsibilities: Design and Develop scalable and resilient data architectures that support business needs, analytics, and AI/ML workloads. Data Pipeline Development: Design and implement robust ETL/ELT processes to ensure efficient data ingestion, transformation, and storage. Big Data & Cloud Solutions: Architect data solutions using cloud platforms like AWS, Azure, or GCP, leveraging services such as Snowflake, Redshift, BigQuery, and Databricks. Database Optimization: Ensure performance tuning, indexing strategies, and query optimization for relational and NoSQL databases. Data Governance & Security: Implement best practices for data quality, metadata management, compliance (GDPR, CCPA), and security. Collaboration & Leadership: Work closely with data engineers, analysts, and business stakeholders to translate business requirements into scalable solutions. Technology Evaluation: Stay updated with emerging trends, assess new tools and frameworks, and drive innovation in data engineering. Required Skills: Education: Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field. Experience: 7 - 12+ years of experience in data engineering Cloud Platforms: Strong expertise in AWS data services. Databases: Hands-on experience with SQL, NoSQL, and columnar databases such as PostgreSQL, MongoDB, Cassandra, and Snowflake. Programming: Proficiency in Python, Scala, or Java for data processing and automation. ETL Tools: Experience with tools like Apache Airflow, Talend, DBT, or Informatica. Machine Learning & AI Integration (Preferred): Understanding of how to architect data solutions for AI/ML applications Show more Show less

We are looking for an experienced Data Engineer having experience in building large-scale data pipelines and data lake ecosystems. Our daily work is around solving interesting and exciting problems against high engineering standards. Even though you will be a part of the backend team, you will be working with cross-functional teams across the org. This role demands good hands-on different programming languages, especially Python, and the knowledge of technologies like Kafka, AWS Glue, Cloudformation, ECS, etc. You will be spending most of your time on facilitating seamless streaming, tracking, and collaborating huge data sets. This is a back-end role, but not limited to it. You will be working closely with producers and consumers of the data and build optimal solutions for the organization. Will appreciate a person with lots of patience and data understanding. Also, we believe in extreme ownership! Design and build systems to efficiently move data across multiple systems and make it available for various teams like Data Science, Data Analytics, and Product. Design, construct, test, and maintain data management systems. Understand data and business metrics required by the product and architect the systems to make that data available in a usable/queryable manner. Ensure that all systems meet the business/company requirements as well as best industry practices. Keep ourselves abreast of new technologies in our domain. Recommend different ways to constantly improve data reliability and quality. Bachelors/Masters, Preferably in Computer Science or a related technical field. 2-5 years of relevant experience. Deep knowledge and working experience of Kafka ecosystem. Good programming experience, preferably in Python, Java, Go, and a willingness to learn more. Experience in working with large sets of data platforms. Strong knowledge of microservices, data warehouse, and data lake systems in the cloud, especially AWS Redshift, S3, and Glue. Strong hands-on experience in writing complex and efficient ETL jobs. Experience in version management systems (preferably with Git). Strong analytical thinking and communication. Passion for finding and sharing best practices and driving discipline for superior data quality and integrity. Intellectual curiosity to find new and unusual ways of how to solve data management issues. Show more Show less

We are seeking a highly experienced AWS Data Solution Architect to lead the design and implementation of scalable, secure, and high-performance data architectures on the AWS cloud. The ideal candidate will have a deep understanding of cloud-based data platforms, analytics, and best practices for optimizing data pipelines and storage. You will work closely with data engineers, business stakeholders, and cloud architects to deliver robust data solutions. Key Responsibilities: 1. Architecture Design and Planning: Design scalable and resilient data architectures on AWS that include data lakes, data warehouses, and real-time processing. Architect end-to-end data solutions leveraging AWS services such as S3, Redshift, RDS, DynamoDB, Glue, and Lake Formation. Develop multi-layered security frameworks for data protection and governance. 2. Data Pipeline Development: Build and optimize ETL/ELT pipelines using AWS Glue, Data Pipeline, and Lambda. Integrate data from various sources like RDBMS, NoSQL, APIs, and streaming platforms. Ensure high availability and real-time processing capabilities for mission-critical applications. 3. Data Warehousing and Analytics: Design and optimize data warehouses using Amazon Redshift or Snowflake. Implement data modeling, partitioning, and indexing for optimal performance. Create analytical models to drive business insights and data-driven decision-making. 4. Real-time Data Processing: Implement real-time data processing using AWS Kinesis, Kafka, or MSK. Architect solutions for event-driven architectures with Lambda and EventBridge. 5. Security and Compliance: Implement best practices for data security, encryption, and access control using IAM, KMS, and Lake Formation. Ensure compliance with regulatory standards like GDPR, HIPAA, and CCPA. 6. Monitoring and Optimization: Monitor performance, optimize costs, and enhance the reliability of data pipelines and storage. Set up observability with AWS CloudWatch, X-Ray, and CloudTrail. Troubleshoot issues and ensure business continuity with automated recovery mechanisms. 7. Documentation and Best Practices: Create detailed architecture diagrams, data flow mappings, and documentation for reference. Establish best practices for data governance, architecture design, and deployment. 8. Collaboration and Leadership: Work closely with data engineers, application developers, and DevOps teams to ensure seamless integration. Act as a technical advisor to business stakeholders for cloud-based data solution Regulatory Compliance Reporting Experience The architect should be able to resolve complex challenges due to the strict regulatory environment in India and the need to balance compliance with operational efficiency. Key complexities include: a) Building data segregation and Access Control capability: This requires in-depth understanding of data privacy laws, Amazon’s global data architecture, and the ability to design systems that can segregate and control access to sensitive payment data without compromising functionality. b) Integrating diverse data sources into Secure Redshift Cluster (SRC) data which involves working with multiple teams and systems, each with its own data structure and transfer protocols. c) Instrumenting additional UPI data elements collaborating with UPI tech teams and a deep understanding of UPI transaction flows to ensure accurate and compliant data capture. d) Automating Law Enforcement Agency (LEA) and Financial Intelligence Unit (FIU) reporting: This involves creating secure, automated pipelines for highly sensitive data, ensuring accuracy and timeliness while meeting strict regulatory requirements. The Architect will be extending from India-specific solutions to serving worldwide markets. Complexities include: a) Designing a unified data storage and compute architecture requiring harmonizing diverse tech stacks and data logging practices across multiple countries while considering data sovereignty laws and cost implications of cross-border data transfers. b) Setting up comprehensive datamarts covering metrics and dimensions involving standardizing metric definitions across markets, ensuring data consistency, and designing for scalability to accommodate future growth. c) Enabling customer segmentation across power-up programs that requires integrating data from diverse programs while maintaining data integrity and respecting country-specific data usage regulations. d) Managing time zone challenges :Synchronizing data across multiple time zones requires innovative solutions to ensure timely data availability without compromising completeness or accuracy. e) Navigating regulatory complexities: Designing systems that comply with varying and evolving data regulations across multiple countries while maintaining operational efficiency and flexibility for future changes. Show more Show less

Hiring: Senior Data Analyst (5+ Years) – Kochi/Trivandrum/Bangalore/Chennai 📍 Location: Kochi / Trivandrum 💰 Budget: Up to 19 LPA 📆 Immediate Joiners Preferred 🚀 About the Role: We’re looking for a Senior Data Analyst to join our Data & Analytics team! You’ll transform complex data into actionable insights, drive strategic decisions, and empower stakeholders with intuitive dashboards and reports. If you love digging into data, solving business problems, and communicating insights effectively, this role is for you! 🔧 Mandatory Key Skills Required: 5 years mandatory ✔ SQL (Advanced) ✔ Power BI (Dashboarding & Visualization) ✔ Python (Data Analysis) ✔ Amazon Athena (or similar cloud data tools) ✔ 5+ years in Data Analysis/Business Intelligence Job Description / Duties & Responsibilities • Collaborate with business stakeholders to understand data needs and translate them into analytical requirements. • Analyze large datasets to uncover trends, patterns, and actionable insights. • Design and build dashboards and reports using Power BI. • Perform ad-hoc analysis and develop data-driven narratives to support decision-making. • Ensure data accuracy, consistency, and integrity through data validation and quality checks. • Build and maintain SQL queries, views, and data models for reporting purposes. • Communicate findings clearly through presentations, visualizations, and written summaries. • Partner with data engineers and architects to improve data pipelines and architecture. • Contribute to the definition of KPIs, metrics, and data governance standards. Job Specification / Skills and Competencies • Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Economics, or a related field. • 5+ years of experience in a data analyst or business intelligence role. • Advanced proficiency in SQL and experience working with relational databases (e.g., SQL Server, Redshift, Snowflake). • Hands-on experience in Power BI. • Proficiency in Python, Excel and data storytelling. • Understanding of data modelling, ETL concepts, and basic data architecture. • Strong analytical thinking and problem-solving skills. • Excellent communication and stakeholder management skills • To adhere to the Information Security Management policies and procedures. Soft Skills Required Must be a good team player with good communication skills Must have good presentation skills Must be a pro-active problem solver and a leader by self Manage & nurture a team of data engineers Show more Show less

Requirements 4+ years of experience as a Data Engineer. Strong proficiency in SQL. Hands-on experience with modern cloud data warehousing solutions (Snowflake, Big Query, Redshift) Expertise in ETL/ELT processes, batch, and streaming data processing. Proven ability to troubleshoot data issues and propose effective solutions. Knowledge of AWS services (S3, DMS, Glue, Athena). Familiarity with DBT for data transformation and modeling. Must be fluent in English communication. Desired Experience Experience with additional AWS services (EC2, ECS, EKS, VPC, IAM). Knowledge of Infrastructure as Code (IaC) tools like Terraform and Terragrunt. Proficiency in Python for data engineering tasks. Experience with orchestration tools like Dagster, Airflow, or AWS Step Functions. Familiarity with pub-sub, queuing, and streaming frameworks (AWS Kinesis, Kafka, SQS, SNS). Experience with CI/CD pipelines and automation for data processes. Skills: sns,data,snowflake,terraform,data engineer,big query,redshift,sqs,dagster,ci,etl,aws step functions,elt,cd,python,aws kinesis,dms,s3,cloud,airflow,ci/cd,dbt,glue,terragrunt,kafka,sql,athena,aws Show more Show less

Requirements 4+ years of experience as a Data Engineer. Strong proficiency in SQL. Hands-on experience with modern cloud data warehousing solutions (Snowflake, Big Query, Redshift) Expertise in ETL/ELT processes, batch, and streaming data processing. Proven ability to troubleshoot data issues and propose effective solutions. Knowledge of AWS services (S3, DMS, Glue, Athena). Familiarity with DBT for data transformation and modeling. Must be fluent in English communication. Desired Experience Experience with additional AWS services (EC2, ECS, EKS, VPC, IAM). Knowledge of Infrastructure as Code (IaC) tools like Terraform and Terragrunt. Proficiency in Python for data engineering tasks. Experience with orchestration tools like Dagster, Airflow, or AWS Step Functions. Familiarity with pub-sub, queuing, and streaming frameworks (AWS Kinesis, Kafka, SQS, SNS). Experience with CI/CD pipelines and automation for data processes. Skills: sns,data,snowflake,terraform,data engineer,big query,redshift,sqs,dagster,ci,etl,aws step functions,elt,cd,python,aws kinesis,dms,s3,cloud,airflow,ci/cd,dbt,glue,terragrunt,kafka,sql,athena,aws Show more Show less

THIS IS A LONG TERM CONTRACT POSITION WITH ONE OF THE LARGEST, GLOBAL, TECHNOLOGY LEADER . Our large, Fortune client is ranked as one of the best companies to work with, in the world. The client fosters progressive culture, creativity, and a Flexible work environment. They use cutting-edge technologies to keep themselves ahead of the curve. Diversity in all aspects is respected. Integrity, experience, honesty, people, humanity, and passion for excellence are some other adjectives that define this global technology leader. Key Responsibilities: Design and maintain robust and scalable data pipeline architecture . Assemble complex data sets that meet both functional and non-functional requirements. Implement internal process improvements, such as automation of manual tasks, optimization of data delivery, and re-designing infrastructure for scale. Build infrastructure to support efficient data extraction, transformation, and loading (ETL) using SQL, dbt , and AWS Big Data technologies . Develop analytics tools to provide actionable insights on employee experience , operational efficiency , and other business performance metrics . Collaborate with stakeholders to resolve data-related issues and support infrastructure needs. Create and manage processes for data transformation, metadata management , and workload orchestration . Stay up to date with emerging cloud technologies (AWS/Azure) and propose opportunities for integration. Partner with Data Scientists and Analysts to enhance data systems and ensure maximum usability. Minimum Qualifications: Bachelor's or Graduate degree in Computer Science , Information Systems , Statistics , or related quantitative field. 5+ years of experience in a Data Engineering role. Extensive hands-on experience with Snowflake and dbt (including advanced concepts like macros and Jinja templating). Proficient in SQL and familiar with various relational databases. Experience in Python and big data frameworks like PySpark . Hands-on experience with AWS services such as S3 , EC2 , Glue , Lambda , RDS , and Redshift . Experience working with APIs for data ingestion and integration. Proven track record in optimizing data pipelines and solving performance issues. Strong analytical and problem-solving skills, with experience conducting root cause analysis . Preferred Qualifications: Experience with AWS CloudFormation templates . Familiarity with Agile/SCRUM methodologies. Exposure to Power BI for dashboard development. Experience working with unstructured datasets and deriving business value from them. Previous experience with globally distributed teams in agile environments. Primary Skills (Must-have): Data Engineering-Data Quality-Data Analysis Show more Show less

At Aramya, we’re redefining fashion for India’s underserved Gen X/Y women, offering size-inclusive, comfortable, and stylish ethnic wear at affordable prices. Launched in 2024, we’ve already achieved ₹40 Cr in revenue in our first year, driven by a unique blend of data-driven design, in-house manufacturing, and a proprietary supply chain. Today, with an ARR of ₹100 Cr, we’re scaling rapidly with ambitious growth plans for the future. Our vision is bold to build the most loved fashion and lifestyle brands across the world while empowering individuals to express themselves effortlessly. Backed by marquee investors like Accel and Z47, we’re on a mission to make high-quality ethnic wear accessible to every woman. We’ve built a community of loyal customers who love our weekly design launches, impeccable quality, and value-for-money offerings. With a fast-moving team driven by creativity, technology, and customer obsession, Aramya is more than a fashion brand—it’s a movement to celebrate every woman’s unique journey. We’re looking for a passionate Data Engineer with a strong foundation. The ideal candidate should have a solid understanding of D2C or e-commerce platforms and be able to work across the stack to build high-performing, user-centric digital experiences. Key Responsibilities Design, build, and maintain scalable ETL/ELT pipelines using tools like Apache Airflow, Databricks , and Spark . Own and manage data lakes/warehouses on AWS Redshift (or Snowflake/BigQuery). Optimize SQL queries and data models for analytics, performance, and reliability. Develop and maintain backend APIs using Python (FastAPI/Django/Flask) or Node.js . Integrate external data sources (APIs, SFTP, third-party connectors) and ensure data quality & validation. Implement monitoring, logging, and alerting for data pipeline health. Collaborate with stakeholders to gather requirements and define data contracts. Maintain infrastructure-as-code (Terraform/CDK) for data workflows and services. Must-Have Skills Strong in SQL and data modeling (OLTP and OLAP). Solid programming experience in Python , preferably for both ETL and backend. Hands-on experience with Databricks , Redshift , or Spark . Experience with building and managing ETL pipelines using tools like Airflow , dbt , or similar. Deep understanding of REST APIs , microservices architecture, and backend design patterns. Familiarity with Docker , Git, CI/CD pipelines. Good grasp of cloud platforms (preferably AWS ) and services like S3, Lambda, ECS/Fargate, CloudWatch. Nice-to-Have Skills Exposure to streaming platforms like Kafka, Kinesis, or Flink. Experience with Snowflake , BigQuery , or Delta Lake . Proficient in data governance , security best practices, and PII handling. Familiarity with GraphQL , gRPC , or event-driven systems. Knowledge of data observability tools (Monte Carlo, Great Expectations, Datafold). Experience working in a D2C/eCommerce or analytics-heavy product environment. Show more Show less

Title: Data Engineer Location: Remote Employment type: Full Time with BayOne We’re looking for a skilled and motivated Data Engineer to join our growing team and help us build scalable data pipelines, optimize data platforms, and enable real-time analytics. What You'll Do Design, develop, and maintain robust data pipelines using tools like Databricks, PySpark, SQL, Fabric, and Azure Data Factory Collaborate with data scientists, analysts, and business teams to ensure data is accessible, clean, and actionable Work on modern data lakehouse architectures and contribute to data governance and quality frameworks Tech Stack Azure | Databricks | PySpark | SQL What We’re Looking For 3+ years experience in data engineering or analytics engineering Hands-on with cloud data platforms and large-scale data processing Strong problem-solving mindset and a passion for clean, efficient data design Job Description: Min 3 years of experience in modern data engineering/data warehousing/data lakes technologies on cloud platforms like Azure, AWS, GCP, Data Bricks etc. Azure experience is preferred over other cloud platforms. 5 years of proven experience with SQL, schema design and dimensional data modelling Solid knowledge of data warehouse best practices, development standards and methodologies Experience with ETL/ELT tools like ADF, Informatica, Talend etc., and data warehousing technologies like Azure Synapse, Microsoft Fabric, Azure SQL, Amazon redshift, Snowflake, Google Big Query etc. Strong experience with big data tools (Databricks, Spark etc..) and programming skills in PySpark and Spark SQL. Be an independent self-learner with “let’s get this done” approach and ability to work in Fast paced and Dynamic environment. Excellent communication and teamwork abilities. Nice-to-Have Skills: Event Hub, IOT Hub, Azure Stream Analytics, Azure Analysis Service, Cosmo DB knowledge. SAP ECC /S/4 and Hana knowledge. Intermediate knowledge on Power BI Azure DevOps and CI/CD deployments, Cloud migration methodologies and processes BayOne is an Equal Opportunity Employer and does not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any federal, state, or local protected class. This job posting represents the general duties and requirements necessary to perform this position and is not an exhaustive statement of all responsibilities, duties, and skills required. Management reserves the right to revise or alter this job description. Show more Show less

TEKsystems is seeking a Senior AWS + Data Engineer to join our dynamic team. The ideal candidate should have expertise Data engineer + Hadoop + Scala/Python with AWS services. This role involves designing, developing, and maintaining scalable and reliable software solutions. Job Title: Data Engineer – Spark/Scala (Batch Processing) Location: Manyata- Hybrid Experience: 7+yrs Type: Full-Time Mandatory Skills: 7-10 years’ experience in design, architecture or development in Analytics and Data Warehousing. Experience in building end-to-end solutions with the Big data platform, Spark or scala programming. 5 years of Solid experience in ETL pipeline building with spark or sclala programming framework with knowledge in developing UNIX Shell Script, Oracle SQL/ PL-SQL. Experience in Big data platform for ETL development with AWS cloud platform. Proficiency in AWS cloud services, specifically EC2, S3, Lambda, Athena, Kinesis, Redshift, Glue , EMR, DynamoDB, IAM, Secret Manager, Step functions, SQS, SNS, Cloud Watch. Excellent skills in Python-based framework development are mandatory. Should have experience with Oracle SQL database programming, SQL performance tuning, and relational model analysis. Extensive experience with Teradata data warehouses and Cloudera Hadoop. Proficient across Enterprise Analytics/BI/DW/ETL technologies such as Teradata Control Framework, Tableau, OBIEE, SAS, Apache Spark, Hive Analytics & BI Architecture appreciation and broad experience across all technology disciplines. Experience in working within a Data Delivery Life Cycle framework & Agile Methodology. Extensive experience in large enterprise environments handling large volume of datasets with High SLAs Good knowledge in developing UNIX scripts, Oracle SQL/PL-SQL, and Autosys JIL Scripts. Well versed in AI Powered Engineering tools like Cline, GitHub Copilo Please send the resumes to nvaseemuddin@teksystems.com or kebhat@teksystems.com Show more Show less

Solution Engineer - Data & AI Mumbai, Maharashtra, India Date posted Jun 16, 2025 Job number 1830869 Work site Up to 50% work from home Travel 25-50 % Role type Individual Contributor Profession Technology Sales Discipline Technology Specialists Employment type Full-Time Overview As a Data Platform Solution Engineer (SE), you will play a pivotal role in helping enterprises unlock the full potential of Microsoft’s cloud database and analytics stack across every stage of deployment. You’ll collaborate closely with engineering leaders and platform teams to accelerate the Fabric Data Platform, including Azure Databases and Analytics, through hands-on engagements like Proof of Concepts, hackathons, and architecture workshops. This opportunity will allow you to accelerate your career growth, develop deep business acumen, hone your technical skills, and become adept at solution design and deployment. You’ll guide customers through secure, scalable solution design, influence technical decisions, and accelerate database and analytics migration into their deployment workflows. In summary, you’ll help customers modernize their data platform and realize the full value of Microsoft’s platform, all while enjoying flexible work opportunities. As a trusted technical advisor, you’ll guide customers through secure, scalable solution design, influence technical decisions, and accelerate database and analytics migration into their deployment workflows. In summary, you’ll help customers modernize their data platform and realize the full value of Microsoft’s platform. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Qualifications 6+ years technical pre-sales, technical consulting, or technology delivery, or related experience OR equivalent experience 4+ years experience with cloud and hybrid, or on premises infrastructure, architecture designs, migrations, industry standards, and/or technology management Proficient on data warehouse & big data migration including on-prem appliance (Teradata, Netezza, Oracle), Hadoop (Cloudera, Hortonworks) and Azure Synapse Gen2. OR 5+ years technical pre-sales or technical consulting experience OR Bachelor's Degree in Computer Science, Information Technology, or related field AND 4+ years technical pre-sales or technical consulting experience OR Master's Degree in Computer Science, Information Technology, or related field AND 3+ year(s) technical pre-sales or technical consulting experience OR equivalent experience Expert on Azure Databases (SQL DB, Cosmos DB, PostgreSQL) from migration & modernize and creating new AI apps. Expert on Azure Analytics (Fabric, Azure Databricks, Purview) and competitors (BigQuery, Redshift, Snowflake) in data warehouse, data lake, big data, analytics, real-time intelligent, and reporting using integrated Data Security & Governance. Proven ability to lead technical engagements (e.g., hackathons, PoCs, MVPs) that drive production-scale outcomes. Responsibilities Drive technical sales with decision makers using demos and PoCs to influence solution design and enable production deployments. Lead hands-on engagements—hackathons and architecture workshops—to accelerate adoption of Microsoft’s cloud platforms. Build trusted relationships with platform leads, co-designing secure, scalable architectures and solutions Resolve technical blockers and objections, collaborating with engineering to share insights and improve products. Maintain deep expertise in Analytics Portfolio: Microsoft Fabric (OneLake, DW, real-time intelligence, BI, Copilot), Azure Databricks, Purview Data Governance and Azure Databases: SQL DB, Cosmos DB, PostgreSQL. Maintain and grow expertise in on-prem EDW (Teradata, Netezza, Exadata), Hadoop & BI solutions. Represent Microsoft through thought leadership in cloud Database & Analytics communities and customer forums Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.  Industry leading healthcare  Educational resources  Discounts on products and services  Savings and investments  Maternity and paternity leave  Generous time away  Giving programs  Opportunities to network and connect Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Solution Engineer - Cloud & Data AI Gurgaon, Haryana, India Date posted Jun 16, 2025 Job number 1830866 Work site Up to 50% work from home Travel 25-50 % Role type Individual Contributor Profession Technology Sales Discipline Technology Specialists Employment type Full-Time Overview As a Data Platform Solution Engineer (SE), you will play a pivotal role in helping enterprises unlock the full potential of Microsoft’s cloud database and analytics stack across every stage of deployment. You’ll collaborate closely with engineering leaders and platform teams to accelerate the Fabric Data Platform, including Azure Databases and Analytics, through hands-on engagements like Proof of Concepts, hackathons, and architecture workshops. This opportunity will allow you to accelerate your career growth, develop deep business acumen, hone your technical skills, and become adept at solution design and deployment. You’ll guide customers through secure, scalable solution design, influence technical decisions, and accelerate database and analytics migration into their deployment workflows. In summary, you’ll help customers modernize their data platform and realize the full value of Microsoft’s platform, all while enjoying flexible work opportunities. As a trusted technical advisor, you’ll guide customers through secure, scalable solution design, influence technical decisions, and accelerate database and analytics migration into their deployment workflows. In summary, you’ll help customers modernize their data platform and realize the full value of Microsoft’s platform. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Qualifications Preffered 6+ years technical pre-sales, technical consulting, or technology delivery, or related experience OR equivalent experience 4+ years experience with cloud and hybrid, or on premises infrastructure, architecture designs, migrations, industry standards, and/or technology management Proficient on data warehouse & big data migration including on-prem appliance (Teradata, Netezza, Oracle), Hadoop (Cloudera, Hortonworks) and Azure Synapse Gen2. Or 5+ years technical pre-sales or technical consulting experience OR Bachelor's Degree in Computer Science, Information Technology, or related field AND 4+ years technical pre-sales or technical consulting experience OR Master's Degree in Computer Science, Information Technology, or related field AND 3+ year(s) technical pre-sales or technical consulting experience OR equivalent experience Expert on Azure Databases (SQL DB, Cosmos DB, PostgreSQL) from migration & modernize and creating new AI apps. Expert on Azure Analytics (Fabric, Azure Databricks, Purview) and other cloud products (BigQuery, Redshift, Snowflake) in data warehouse, data lake, big data, analytics, real-time intelligent, and reporting using integrated Data Security & Governance. Proven ability to lead technical engagements (e.g., hackathons, PoCs, MVPs) that drive production-scale outcomes. Responsibilities Drive technical conversations with decision makers using demos and PoCs to influence solution design and enable production deployments. Lead hands-on engagements—hackathons and architecture workshops—to accelerate adoption of Microsoft’s cloud platforms. Build trusted relationships with platform leads, co-designing secure, scalable architectures and solutions Resolve technical blockers and objections, collaborating with engineering to share insights and improve products. Maintain deep expertise in Analytics Portfolio: Microsoft Fabric (OneLake, DW, real-time intelligence, BI, Copilot), Azure Databricks, Purview Data Governance and Azure Databases: SQL DB, Cosmos DB, PostgreSQL. Maintain and grow expertise in on-prem EDW (Teradata, Netezza, Exadata), Hadoop & BI solutions. Represent Microsoft through thought leadership in cloud Database & Analytics communities and customer forums Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.  Industry leading healthcare  Educational resources  Discounts on products and services  Savings and investments  Maternity and paternity leave  Generous time away  Giving programs  Opportunities to network and connect Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Noida, Uttar Pradesh, India Business Intelligence BOLD is seeking for QA professional who will work directly with the BI Development team to validate Business Intelligence solutions. He will build test strategy and test plans and test cases for ETL and Business Intelligence components. He will also validate SQL queries related to test cases and produce test summary reports. Job Description ABOUT THIS TEAM BOLD Business Intelligence(BI) team is a centralized team responsible for managing all aspects of the organization's BI strategy, projects and systems. BI team enables business leaders to make data-driven decisions by providing reports and analysis. The team is responsible for developing and manage a latency-free credible enterprise data warehouse which is a data source for decision making and input to various functions of the organization like Product, Finance, Marketing, Customer Support etc. BI team has four sub-components as Data analysis, ETL, Data Visualization and QA. It manages deliveries through Snowflake, Sisense and Microstrategy as main infrastructure solutions. Other technologies including Python, R, Airflow are also used in ETL, QA and data visualizations. WHAT YOU’LL DO Work with Business Analysts, BI Developers to translate Business requirements into Test Cases Responsible for validating the data sources, extraction of data, applying transformation logic, and loading the data in the target tables. Designing, documenting and executing test plans, test harness, test scenarios/scripts & test cases for manual, automated & bug tracking tools. WHAT YOU’LL NEED Experience in Data Warehousing / BI Testing, using any ETL and Reporting Tool Extensive experience in writing and troubleshooting SQL Queries using any of the Databases – Snowflake/ Redshift / SQL Server / Oracle Exposure to Data Warehousing and Dimensional Modelling Concepts Experience in understanding of ETL Source to Target Mapping Document Experience in testing the code on any of the ETL Tools Experience in Validating the Dashboards / Reports on any of the Reporting tools – Sisense / Tableau / SAP Business Objects / MicroStrategy Hands-on experience and strong understanding of Software Development Life Cycle (SDLC) and Software Testing Life Cycle (STLC). Good experience of Quality Assurance methodologies like Waterfall, V-Model, Agile, Scrum. Well versed with writing detailed test cases for functional & non-functional requirements. Experience on different types of testing that includes Black Box testing, Smoke testing, Functional testing, System Integration testing, End-to-End Testing, Regression testing & User Acceptance testing (UAT) & Involved in Load Testing, Performance Testing & Stress Testing. · Expertise in using TFS / JIRA / Excel for writing the Test Cases and tracking the Exposure in scripting languages like Python to create automated Test Scripts or Automated tools like Query Surge will be an added advantage An effective communicator with strong analytical abilities combined with skills to plan, implement & presentation of projects EXPERIENCE- Senior QA Engineer, BI: 4.5 years+ #LI-SV1 Benefits Outstanding Compensation Competitive salary Tax-friendly compensation structure Bi-annual bonus Annual Appraisal Equity in company 100% Full Health Benefits Group Mediclaim, personal accident, & term life insurance Group Mediclaim benefit (including parents' coverage) Practo Plus health membership for employees and family Personal accident and term life insurance coverage Flexible Time Away 24 days paid leaves Declared fixed holidays Paternity and maternity leave Compassionate and marriage leave Covid leave (up to 7 days) Additional Benefits Internet and home office reimbursement In-office catered lunch, meals, and snacks Certification policy Cab pick-up and drop-off facility About BOLD We Transform Work Lives As an established global organization, BOLD helps people find jobs. Our story is one of growth, success, and professional fulfillment. We create digital products that have empowered millions of people in 180 countries to build stronger resumes, cover letters, and CVs. The result of our work helps people interview confidently, finding the right job in less time. Our employees are experts, learners, contributors, and creatives. We Celebrate And Promote Diversity And Inclusion We value our position as an Equal Opportunity Employer. We hire based on qualifications, merit, and our business needs. We don't discriminate regarding race, color, religion, gender, pregnancy, national origin or citizenship, ancestry, age, physical or mental disability, veteran status, sexual orientation, gender identity or expression, marital status, genetic information, or any other applicable characteristic protected by law.