8333 Kafka Jobs - Page 6

Sprinklr is a leading enterprise software company for all customer-facing functions. With advanced AI, Sprinklr's unified customer experience management (Unified-CXM) platform helps companies deliver human experiences to every customer, every time, across any modern channel. Headquartered in New York City with employees around the world, Sprinklr works with more than 1,000 of the world’s most valuable enterprises - global brands like Microsoft, P&G, Samsung and more than 50% of the Fortune 100. What Does Success Look Like? We are looking for a Senior Engineering Manager to lead and scale a team of high-caliber backend and platform engineers building distributed systems that power our mission-critical CCaaS product. As a technical leader and people manager, you’ll be responsible for both technical excellence and organizational health - driving architecture, execution, and team growth in a fast-paced, product-led SaaS environment. This is a high-impact role for someone who thrives on solving complex engineering problems at scale, enabling a team to operate at their peak, and building platforms that directly drive business outcomes. Seniority Level: Senior Manager / Hands-on People C Technical Leader Reports to: Director of Engineering or VP Engineering Team Size: 8–15 Engineers (Leads + ICs) Technology Stack: Java, Spring Boot, Kafka, Redis, MongoDB, Postgres, Kubernetes, AWS What You’ll Do: Technical Leadership: Lead design and delivery of scalable, distributed backend systems and real-time platform APIs using Java-based microservices. Partner with Architects and Tech Leads to establish technical vision, system design, and long-term architecture . Drive engineering excellence through code reviews, design reviews, observability, performance tuning, and SLAs . Own end-to-end system reliability, scalability, cost, and maintainability. People Management: Manage, coach, and grow a team of backend engineers across levels. Drive career development , technical mentoring , and regular 1:1s . Foster a high-performance, inclusive culture grounded in ownership, autonomy, and accountability. Recruit and onboard exceptional engineering talent; collaborate with TA and interview panel on hiring strategy. Executions Delivery: Drive sprint planning, estimation, and delivery across multiple squads or initiatives. Partner with Product and Program Managers to align engineering execution with business goals. Set and monitor engineering OKRs , team velocity, and project health metrics. Proactively identify tech debt, risks, and improvement areas. Cross-Functional Collaboration: Work closely with Product, DevOps, QA, and Customer Support teams to ensure end-to-end solution delivery. Represent Engineering in roadmap planning, executive reviews, and customer- facing discussions (when needed) What Makes You Qualified? 8 to 12 years of total experience, with at least 2+ years in engineering leadership roles . Deep experience designing, building, and operating Java-based microservices in cloud-native, distributed environments . Strong understanding of backend architectural patterns. Proven track record of building and scaling high-performing engineering teams . Experience with Kafka, Redis, MongoDB/PostgreSQL, Spring Boot, Kubernetes, REST APIs, CI/CD pipelines. Strong communication and stakeholder management skills Show more Show less

🚀 Job Opening: Full Stack Developer 📍 Location: Mumbai, India 📩 Apply Now: hr@victreesolutions.com #FullStackDeveloper #Java #ReactJS #Microservices #Kafka #Angular #Docker #SpringBoot #HiringNow Role Overview: We are looking for a passionate and skilled Full Stack Developer to join our dynamic development team. You will be responsible for building scalable, robust, and dynamic front-end and back-end solutions, primarily using Java and modern JS frameworks. Key Responsibilities: Analyze requirements and perform impact analysis. Design and develop dynamic front-end and back-end applications. Collaborate with product managers and cross-functional teams. Prepare software releases and maintain continuous improvements. Stay up-to-date with emerging tools, frameworks, and tech practices. Core Technical Skills Required: Proficient in Java 8 , Spring Boot , and Microservices Architecture Experience with Kafka and gRPC Strong understanding of REST APIs , HTML/CSS/JavaScript Solid hands-on with ReactJS (incl. React Hooks), NPM Familiarity with Docker , Kubernetes , and Cloud platforms (AWS, Azure, GCP) Experience with SQL and NoSQL databases Nice to Have: Knowledge of WebSockets , Java Threads , Executor Service , and Lightstreamer Experience with Node.js , Maven , Git, and Design Patterns What We Offer: Opportunity to work on cutting-edge tech in a niche industry Collaborative and inclusive team environment Fast-paced, learning-focused culture If you're passionate about full stack development and want to work on impactful enterprise software solutions, we'd love to hear from you! 📩 Send your resume to: hr@victreesolutions.com 🕒 Apply ASAP – Limited Positions Available! Show more Show less

Role Summary We are seeking a highly motivated and skilled Data Engineer to join our data and analytics team. This role is ideal for someone with strong experience in building scalable data pipelines, working with modern lakehouse architectures, and deploying data solutions on Microsoft Azure. You’ll be instrumental in developing, orchestrating, and maintaining our real-time and batch data infrastructure using tools like Apache Spark, Apache Kafka, Apache Airflow, Azure Data Services, and modern DevOps practices. Key Responsibilities Design and implement ETL/ELT data pipelines for structured and unstructured data using Azure Data Factory, Databricks, or Apache Spark. Work with Azure Blob Storage, Data Lake, and Synapse Analytics to build scalable data lakes and warehouses. Develop real-time data ingestion pipelines using Apache Kafka, Apache Flink, or Apache Beam. Build and schedule jobs using orchestration tools like Apache Airflow or Dagster. Perform data modeling using Kimball methodology for building dimensional models in Snowflake or other data warehouses. Implement data versioning and transformation using DBT and Apache Iceberg or Delta Lake. Manage data cataloging and lineage using tools like Marquez or Collibra. Collaborate with DevOps teams to containerize solutions using Docker, manage infrastructure with Terraform, and deploy on Kubernetes. Setup and maintain monitoring and alerting systems using Prometheus and Grafana for performance and reliability. Required Skills & Qualifications Programming & Scripting: Proficiency in Python, with strong knowledge of OOP and data structures & algorithms. Comfortable working in Linux environments for development and deployment. Database Technologies: Strong command over SQL and understanding of relational (DBMS) and NoSQL databases. Big Data & Real-Time Processing: Solid experience with Apache Spark (PySpark/Scala). Familiarity with real-time processing tools like Kafka, Flink, or Beam. Orchestration & Scheduling: Hands-on experience with Airflow, Dagster, or similar orchestration tools. Cloud Platform: Deep experience with Microsoft Azure, especially Azure Data Factory, Blob Storage, Synapse, Azure Functions, etc. AZ-900 or other Azure certifications are a plus. Lakehouse & Warehousing Knowledge of dimensional modeling, Snowflake, Apache Iceberg, and Delta Lake. Understanding of modern Lakehouse architecture and related best practices. Data Cataloging & Governance Familiarity with Marquez, Collibra, or other cataloging tools. DevOps & CI/CD Experience with Terraform, Docker, Kubernetes, and Jenkins or equivalent CI/CD tools. Monitoring & Logging Proficiency in setting up dashboards and alerts with Prometheus and Grafana. Note: - Immediate joiner will be preferred. Show more Show less

Role - Java Developer Experience - 3-5 yrs Location - Bangalore Backend ● Bachelors/Masters in Computer science from a reputed institute/university ● 3-7 years of strong experience in building Java/golang/python based server side solutions ● Strong in data structure, algorithm and software design ● Experience in designing and building RESTful micro services ● Experience with Server side frameworks such as JPA (HIbernate/SpringData), Spring, vertex, Springboot, Redis, Kafka, Lucene/Solr/ElasticSearch etc. ● Experience in data modeling and design, database query tuning ● Experience in MySQL and strong understanding of relational databases. ● Comfortable with agile, iterative development practices ● Excellent communication (verbal & written), interpersonal and leadership skills ● Previous experience as part of a Start-up or a Product company. ● Experience with AWS technologies would be a plus ● Experience with reactive programming frameworks would be a plus · Contributions to opensource are a plus ● Familiarity with deployment architecture principles and prior experience with container orchestration platforms, particularly Kubernetes, would be a significant advantage Show more Show less

We are hiring for one of our client for Automation QA for Bangalore - Marathahalli location. Location : Bangalore - Marathahalli (Hybrid) Experience : 5-9 Years Budget : 27 LPA Mandate Skills : Python , AWS , Any Framework , Selenium , Kafka (Knowledge), AI/ML(Gen AI etc..). Technical Skills: Proven experience in building automation frameworks for both frontend and backend systems. Hands-on experience with AWS services such as EC2, S3, Lambda, and Kafka. Strong understanding of Kafka, including producing and consuming messages for test automation. Hands-on experience with AI/ML tools for automation, such as Testim, Mabl, Functionize, or custom AI models (e.g., for NLP-based test generation or failure prediction). Prior experience in setting up AI-based test data generation. Experience in Python programming language. Familiarity with test automation tools and frameworks like Robot framework, Playwright, Selenium or similar. Strong understanding of REST APIs and API testing tools like Postman, Rest Assured etc.. Experience with CI/CD pipelines and tools such as Jenkins, GitLab etc Exposure to Graph DB, MongoDB, and Cassandra. Knowledge of Docker/Kubernetes is a plus Excellent problem-solving skills and attention to detail. Experience working in Agile projects Strong communication and collaboration skills to work effectively in a team environment. Essential Skills 1. Building automation frameworks for both frontend and backend systems. 2. Python Programing 3. AWS services such as EC2, S3, Lambda 4. Strong understanding of Kafka 5. AI/ML tools for automation, such as Testim, Mabl, Functionize (Good to have) 1. Experience with CI/CD pipelines 2. test automation tools and frameworks like Robot framework, Playwright, Selenium or similar. 3. Knowledge of Docker/Kubernetes

LEAD DATA ENGINEER Location: Hyderabad Role: Permanent Mode: WFO JOB RESPONSIBILITIES: Tracks the various Machine learning projects and their data needs. Tracks and improves Kanban process of product maintenance Drives complex technical discussions both within company and outside data partners Actively Contributes to the design of machine learning solutions by having a deep understanding of how the data is used and how new sources of data can be introduced Advocates for investments in tools and technologies to streamline data workflows and reduce technical debt Continuously explores and adopts emerging technologies and methodologies in data engineering and machine learning Develops and maintains scalable data pipelines to support machine learning models and analytics Collaborates with data scientists to ensure efficient data processing and model deployment Ensures data quality, integrity, and security across all stages of the data pipeline Implements monitoring and alerting systems to detect anomalies in data processing and model performance Enhances data versioning, data lineage, and reproducibility practices to improve model transparency and auditing . QUALIFICATION 5+ years of experience in data engineering or related fields, with a strong focus on building scalable data pipelines to support machine learning workflows. Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or other relevant fields. Specific experience in Kafka needed . Snowflake and data bricks would be huge plus. Proven expertise in designing, implementing, and maintaining large-scale, high-performance data architectures and ETL processes managing 1TB a day. Strong knowledge of database management systems (SQL and NoSQL), distributed data processing (e.g., Hadoop, Spark), and cloud platforms (AWS, GCP, Azure). Experience working closely with data scientists and machine learning engineers to optimize data flows for model training and real-time inference with latency requirements. Hands-on experience with data wrangling, data preprocessing, and feature engineering to ensure clean, high-quality data for machine learning models. Solid understanding of data governance, security protocols, and compliance requirements (e.g., GDPR, HIPAA) to ensure data privacy and integrity. Preferred Experience in data pipelines and analytics for video-game development Experience in Advertising industry Experience in online businesses where transactions happen without human intervention. Show more Show less

Job Summary We are seeking an experienced Data Architect with expertise in Snowflake, dbt, Apache Airflow, and AWS to design, implement, and optimize scalable data solutions. The ideal candidate will play a critical role in defining data architecture, governance, and best practices while collaborating with cross-functional teams to drive data-driven decision-making. Key Responsibilities Data Architecture & Strategy: Design and implement scalable, high-performance cloud-based data architectures on AWS. Define data modelling standards for structured and semi-structured data in Snowflake. Establish data governance, security, and compliance best practices. Data Warehousing & ETL/ELT Pipelines: Develop, maintain, and optimize Snowflake-based data warehouses. Implement dbt (Data Build Tool) for data transformation and modelling. Design and schedule data pipelines using Apache Airflow for orchestration. Cloud & Infrastructure Management: Architect and optimize data pipelines using AWS services like S3, Glue, Lambda, and Redshift. Ensure cost-effective, highly available, and scalable cloud data solutions. Collaboration & Leadership: Work closely with data engineers, analysts, and business stakeholders to align data solutions with business goals. Provide technical guidance and mentoring to the data engineering team. Performance Optimization & Monitoring: Optimize query performance and data processing within Snowflake. Implement logging, monitoring, and alerting for pipeline reliability. Required Skills & Qualifications 10+ years of experience in data architecture, engineering, or related roles. Strong expertise in Snowflake, including data modeling, performance tuning, and security best practices. Hands-on experience with dbt for data transformations and modeling. Proficiency in Apache Airflow for workflow orchestration. Strong knowledge of AWS services (S3, Glue, Lambda, Redshift, IAM, EC2, etc.). Experience with SQL, Python, or Spark for data processing. Familiarity with CI/CD pipelines, Infrastructure-as-Code (Terraform/CloudFormation) is a plus. Strong understanding of data governance, security, and compliance (GDPR, HIPAA, etc.). Preferred Qualifications Certifications: AWS Certified Data Analytics – Specialty, Snowflake SnowPro Certification, or dbt Certification. Experience with streaming technologies (Kafka, Kinesis) is a plus. Knowledge of modern data stack tools (Looker, Power BI, etc.). Experience in OTT streaming could be added advantage. Show more Show less

We are hiring for Micro Services Sr Developer. Role: Micro Services Sr Developer Experience: 4 years to 8 years Location: Hyderabad/Kolkata Technical skill-Java 8, Springboot, Microservices Interested candidates can send their resume on below mail ID along with below details- geethanjali.u@tcs.com Please share below details- Full Name: Email: Contact Details: Total Experience: Current location: Preferred location: Relevant Experience: Notice Period: Current CTC: Expected CTC: Current Company Name: Education or career gap (if any): EP Reference Number (if already registered with TCS) – Highest Qualification: Highest Qualification University Name: Must Have- Core Java, Java 8 2. Spring Core 3. Springboot 4. Microservices 5. ORM(Hibernate, JPA etc,.) 6. ReSTFul services 8. Programming exp atleast 3 yrs 9. Attitude to upskill 10. Communication Good to have- Any cloud experience(GCP, AWS, Azure) Knowledge on Kafka Database usage experience(Oracle/DB2) 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

Back-End Engineer – Go + PostgreSQL (Contract) Core Skills (“Must-Have”) Golang expertise Idiomatic Go 1.21+, goroutines / channels, std-lib HTTP & sql packages, context-aware code Relational-data mastery Hands-on with PostgreSQL 13+ — schema design, indexes, migrations (Flyway, Goose, or pg-migrate) Comfortable writing performant SQL and debugging query plans API craftsmanship Design and version REST/JSON (or gRPC) endpoints; enforce contract tests and backward compatibility Quality & Dev-Ops hygiene Unit + integration tests (Go test / Testcontainers), GitHub Actions or similar CI, Docker-ised local setup Observability hooks (Prometheus metrics, structured logging, Sentry) Collaboration fluency Pair daily with React front-end & designers; discuss payloads, edge cases, and rollout plans up front Day-to-Day Responsibilities Ship incremental data-model and API updates — e.g., add a column with default values, write safe up/down migrations, expose the field in existing endpoints, and coordinate UI changes Design small new features such as derived “metric-health” tables or aggregated views that power dashboards Guard performance & reliability — run load tests, add indexes, set query timeouts, and handle graceful fallbacks behind feature flags Keep codebase clean — review PRs, refactor shared helpers, and prune dead code as product evolves Nice-to-Have Extras Production experience with a feature-flag SDK (LaunchDarkly, Split, etc.) to stage database changes safely Familiarity with event streaming (Kafka / NATS) or background job runners (Go workers, Sidekiq-like queues) Exposure to container orchestration (Kubernetes, ECS) and infrastructure-as-code (Terraform, Pulumi) Sample Mini-Projects You Might Tackle Scenario: Add property to existing entity Write migration to add source_type column to metrics, backfill with default, update GET/POST /metrics handlers & swagger docs, unit-test both happy & error paths Scenario: New aggregated view Create new table metric_health that rolls up pass/fail counts per metric, expose /metrics/{id}/health endpoint returning red/amber/green status with pagination, instrument with Prometheus counters Show more Show less

About Lemongrass Lemongrass is a software-enabled services provider, synonymous with SAP on Cloud, focused on delivering superior, highly automated Managed Services to Enterprise customers. Our customers span multiple verticals and geographies across the Americas, EMEA and APAC. We partner with AWS, SAP, Microsoft and other global technology leaders. We are seeking an experienced Cloud Data Engineer with a strong background in AWS, Azure, and GCP. The ideal candidate will have extensive experience with cloud-native ETL tools such as AWS DMS, AWS Glue, Kafka, Azure Data Factory, GCP Dataflow, and other ETL tools like Informatica, SAP Data Intelligence, etc. You will be responsible for designing, implementing, and maintaining robust data pipelines and building scalable data lakes. Experience with various data platforms like Redshift, Snowflake, Databricks, Synapse, Snowflake and others is essential. Familiarity with data extraction from SAP or ERP systems is a plus. Key Responsibilities: Design and Development: Design, develop, and maintain scalable ETL pipelines using cloud-native tools (AWS DMS, AWS Glue, Kafka, Azure Data Factory, GCP Dataflow, etc.). Architect and implement data lakes and data warehouses on cloud platforms (AWS, Azure, GCP). Develop and optimize data ingestion, transformation, and loading processes using Databricks, Snowflake, Redshift, BigQuery and Azure Synapse. Implement ETL processes using tools like Informatica, SAP Data Intelligence, and others. Develop and optimize data processing jobs using Spark Scala. Data Integration and Management: Integrate various data sources, including relational databases, APIs, unstructured data, and ERP systems into the data lake. Ensure data quality and integrity through rigorous testing and validation. Perform data extraction from SAP or ERP systems when necessary. Performance Optimization: Monitor and optimize the performance of data pipelines and ETL processes. Implement best practices for data management, including data governance, security, and compliance. Collaboration and Communication: Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions. Collaborate with cross-functional teams to design and implement data solutions that meet business needs. Documentation and Maintenance: Document technical solutions, processes, and workflows. Maintain and troubleshoot existing ETL pipelines and data integrations. Qualifications Education: Bachelor’s degree in Computer Science, Information Technology, or a related field. Advanced degrees are a plus. Experience: 7+ years of experience as a Data Engineer or in a similar role. Proven experience with cloud platforms: AWS, Azure, and GCP. Hands-on experience with cloud-native ETL tools such as AWS DMS, AWS Glue, Kafka, Azure Data Factory, GCP Dataflow, etc. Experience with other ETL tools like Informatica, SAP Data Intelligence, etc. Experience in building and managing data lakes and data warehouses. Proficiency with data platforms like Redshift, Snowflake, BigQuery, Databricks, and Azure Synapse. Experience with data extraction from SAP or ERP systems is a plus. Strong experience with Spark and Scala for data processing. Skills: Strong programming skills in Python, Java, or Scala. Proficient in SQL and query optimization techniques. Familiarity with data modeling, ETL/ELT processes, and data warehousing concepts. Knowledge of data governance, security, and compliance best practices. Excellent problem-solving and analytical skills. Strong communication and collaboration skills. Preferred Qualifications: Experience with other data tools and technologies such as Apache Spark, or Hadoop. Certifications in cloud platforms (AWS Certified Data Analytics – Specialty, Google Professional Data Engineer, Microsoft Certified: Azure Data Engineer Associate). Experience with CI/CD pipelines and DevOps practices for data engineering Selected applicant will be subject to a background investigation, which will be conducted and the results of which will be used in compliance with applicable law. What we offer in return: Remote Working: Lemongrass always has been and always will offer 100% remote work Flexibility: Work where and when you like most of the time Training: A subscription to A Cloud Guru and generous budget for taking certifications and other resources you’ll find helpful State of the art tech: An opportunity to learn and run the latest industry standard tools Team: Colleagues who will challenge you giving the chance to learn from them and them from you Lemongrass Consulting is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate on the basis of race, religion, color, national origin, religious creed, gender, sexual orientation, gender identity, gender expression, age, genetic information, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics Show more Show less

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

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

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

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

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

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

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

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

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

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

We are looking forward to hire FullStack (Java + Angular+AWS) professionals at the level of Sr.Software Engineer, who thrive on challenges and desire to make a real difference in the business world. With an environment of extraordinary innovation and unprecedented growth, this is an exciting opportunity for a self-starter who enjoys working in a fast-paced, quality-oriented, and team environment. You are required to have skills in the following areas : Minimum 5 years of experience in Java and related technologies Good understanding for Spring framework - Spring core, MVC, Boot, Microservices pattern. Working knowledge of building Micro Services, RESTful web Services using any framework (Spring Boot, JaxRS, Jersey) Hands on experience in web services development and solid understanding of Java web technologies using Java 8 Solid understanding of UI basics HTML, CSS, Java script, jQuery, Ajax Hands-on on Typescript and Angular 9+ with modular architecture. Good understanding of Message Queues and have worked upon any one of them (Kafka / RabbitMQ / ActiveMQ) Expertise in Relational database (MySQL / MS SQL /Oracle) o Working experience in Devops Build Tools – Maven / Gradle Version control - Git, GitHub / Bitbucket CI/CD - Jenkins, Ansible, Artifactory Good understanding in building & deploying application on the AWS cloud platform Understanding and expertise in maintaining Code quality (TDD, JUnit, Mockito, Power Mock, SonarQube, Sonar lint) Working knowledge of Agile process and tools – Scrum / Kanban, Jira, Confluence Proficiency in Interpersonal skills, Problem solving, Planning & execution and Impactful communication. Positive, flexible, learning and can do attitude. We are looking forward to hire Java Full-Stack (Java + Angular) professionals at the level of Sr. Software Engineer, who thrive on challenges and desire to make a real difference in the business world. With an environment of extraordinary innovation and unprecedented growth, this is an exciting opportunity for a self-starter who enjoys working in a fast-paced, quality-oriented, and team environment. You are required to have skills in the following areas: Minimum 5 years of experience in Java and related technologies Good understanding for Spring framework - Spring core, MVC, Boot, Microservices pattern. Working knowledge of building Micro Services, RESTful web Services using any framework (Spring Boot, JaxRS, Jersey) Hands-on experience in web services development and solid understanding of Java web technologies using Java 8 Solid understanding of UI basics HTML, CSS, Java script, jQuery, Ajax Typescript and Angular 9+ with modular architecture. Minimum 2 + of working experience in UI Designing using Angular Framework along with knowledge on Jasmine/Karma. Good understanding of Message Queues and have worked on any one of them (Kafka / RabbitMQ / ActiveMQ) Expertise in Relational databases (MySQL / MS SQL /Oracle) or NoSQL Database. Working experience in DevOps Build Tools – Maven / Gradle Version control - Git, GitHub / Bitbucket CI/CD - Jenkins, Ansible, Artifactory Good understanding of building & deploying applications on the AWS cloud platform Understanding and expertise in maintaining Code quality (TDD, JUnit, Mockito, Power Mock, SonarQube, Sonar lint) Working knowledge of Agile processes and tools – Scrum / Kanban, Jira, Confluence Proficiency in Interpersonal skills, Problem-solving, Planning & execution, and Impactful communication. Positive, flexible, learning, and can-do attitude. We are looking forward to hire FullStack (Java + Angular+AWS) professionals at the level of Sr.Software Engineer, who thrive on challenges and desire to make a real difference in the business world. With an environment of extraordinary innovation and unprecedented growth, this is an exciting opportunity for a self-starter who enjoys working in a fast-paced, quality-oriented, and team environment. You are required to have skills in the following areas : Minimum 5 years of experience in Java and related technologies Good understanding for Spring framework - Spring core, MVC, Boot, Microservices pattern. Working knowledge of building Micro Services, RESTful web Services using any framework (Spring Boot, JaxRS, Jersey) Hands on experience in web services development and solid understanding of Java web technologies using Java 8 Solid understanding of UI basics HTML, CSS, Java script, jQuery, Ajax Hands-on on Typescript and Angular 9+ with modular architecture. Good understanding of Message Queues and have worked upon any one of them (Kafka / RabbitMQ / ActiveMQ) Expertise in Relational database (MySQL / MS SQL /Oracle) o Working experience in Devops Build Tools – Maven / Gradle Version control - Git, GitHub / Bitbucket CI/CD - Jenkins, Ansible, Artifactory Good understanding in building & deploying application on the AWS cloud platform Understanding and expertise in maintaining Code quality (TDD, JUnit, Mockito, Power Mock, SonarQube, Sonar lint) Working knowledge of Agile process and tools – Scrum / Kanban, Jira, Confluence Proficiency in Interpersonal skills, Problem solving, Planning & execution and Impactful communication. Positive, flexible, learning and can do attitude. 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

Eviden, part of the Atos Group, with an annual revenue of circa € 5 billion is a global leader in data-driven, trusted and sustainable digital transformation. As a next generation digital business with worldwide leading positions in digital, cloud, data, advanced computing and security, it brings deep expertise for all industries in more than 47 countries. By uniting unique high-end technologies across the full digital continuum with 47,000 world-class talents, Eviden expands the possibilities of data and technology, now and for generations to come. Role Overview The Senior Tech Lead - AWS Data Engineering leads the design, development and optimization of data solutions on the AWS platform. The jobholder has a strong background in data engineering, cloud architecture, and team leadership, with a proven ability to deliver scalable and secure data systems. Responsibilities Lead the design and implementation of AWS-based data architectures and pipelines. Architect and optimize data solutions using AWS services such as S3, Redshift, Glue, EMR, and Lambda. Provide technical leadership and mentorship to a team of data engineers. Collaborate with stakeholders to define project requirements and ensure alignment with business goals. Ensure best practices in data security, governance, and compliance. Troubleshoot and resolve complex technical issues in AWS data environments. Stay updated on the latest AWS technologies and industry trends. Key Technical Skills & Responsibilities Overall 10+Yrs of Experience in IT Minimum 5-7 years in design and development of cloud data platforms using AWS services Must have experience of design and development of data lake / data warehouse / data analytics solutions using AWS services like S3, Lake Formation, Glue, Athena, EMR, Lambda, Redshift Must be aware about the AWS access control and data security features like VPC, IAM, Security Groups, KMS etc Must be good with Python and PySpark for data pipeline building. Must have data modeling including S3 data organization experience Must have an understanding of hadoop components, No SQL database, graph database and time series database; and AWS services available for those technologies Must have experience of working with structured, semi-structured and unstructured data Must have experience of streaming data collection and processing. Kafka experience is preferred. Experience of migrating data warehouse / big data application to AWS is preferred . Must be able to use Gen AI services (like Amazon Q) for productivity gain Eligibility Criteria Bachelor’s degree in Computer Science, Data Engineering, or a related field. Extensive experience with AWS data services and tools. AWS certification (e.g., AWS Certified Data Analytics - Specialty). Experience with machine learning and AI integration in AWS environments. Strong understanding of data modeling, ETL/ELT processes, and cloud integration. Proven leadership experience in managing technical teams. Excellent problem-solving and communication skills. Our Offering Global cutting-edge IT projects that shape the future of digital and have a positive impact on environment. Wellbeing programs & work-life balance - integration and passion sharing events. Attractive Salary and Company Initiative Benefits Courses and conferences Attractive Salary Hybrid work culture Let’s grow together. Show more Show less

So, what’s the role all about? We are looking for a highly driven and technically skilled Software Engineer to lead the integration of various Content Management Systems with AWS Knowledge Hub, enabling advanced Retrieval-Augmented Generation (RAG) search across heterogeneous customer data—without requiring data duplication. This role will also be responsible for expanding the scope of Knowledge Hub to support non-traditional knowledge items and enhance customer self-service capabilities. You will work at the intersection of AI, search infrastructure, and developer experience to make enterprise knowledge instantly accessible, actionable, and AI-ready. How will you make an impact? Integrate CMS with AWS Knowledge Hub to allow seamless RAG-based search across diverse data types—eliminating the need to copy data into Knowledge Hub instances. Extend Knowledge Hub capabilities to ingest and index non-knowledge assets, including structured data, documents, tickets, logs, and other enterprise sources. Build secure, scalable connectors to read directly from customer-maintained indices and data repositories. Enable self-service capabilities for customers to manage content sources using App Flow, Tray.ai, configure ingestion rules, and set up search parameters independently. Collaborate with the NLP/AI team to optimize relevance and performance for RAG search pipelines. Work closely with product and UX teams to design intuitive, powerful experiences around self-service data onboarding and search configuration. Implement data governance, access control, and observability features to ensure enterprise readiness. Have you got what it takes? Proven experience with search infrastructure, RAG pipelines, and LLM-based applications. 2+ Years’ hands-on experience with AWS Knowledge Hub, AppFlow, Tray.ai, or equivalent cloud-based indexing/search platforms. Strong backend development skills (Python, Typescript/NodeJS, .NET/Java) and familiarity with building and consuming REST APIs. Infrastructure as a code (IAAS) service like AWS Cloud formation, CDK knowledge Deep understanding of data ingestion pipelines, index management, and search query optimization. Experience working with unstructured and semi-structured data in real-world enterprise settings. Ability to design for scale, security, and multi-tenant environment. What’s in it for you? Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NICEr! Enjoy NICE-FLEX! At NICE, we work according to the NICE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere. Reporting into: Tech Manager, Engineering, CX Role Type: Individual Contributor