2785 Airflow Jobs - Page 2

Location: Ahmedabad / Pune Required Experience: 5+ Years Preferred Immediate Joiner We are looking for a highly skilled Lead Data Engineer (Snowflake) to join our team. The ideal candidate will have extensive experience Snowflake, and cloud platforms, with a strong understanding of ETL processes, data warehousing concepts, and programming languages. If you have a passion for working with large datasets, designing scalable database schemas, and solving complex data problems. Key Responsibilities: Design, implement, and optimize data pipelines and workflows using Apache Airflow Develop incremental and full-load strategies with monitoring, retries, and logging Build scalable data models and transformations in dbt, ensuring modularity, documentation, and test coverage Develop and maintain data warehouses in Snowflake Ensure data quality, integrity, and reliability through validation frameworks and automated testing Tune performance through clustering keys, warehouse scaling, materialized views, and query optimization. Monitor job performance and resolve data pipeline issues proactively Build and maintain data quality frameworks (null checks, type checks, threshold alerts). Partner with data analysts, scientists, and business stakeholders to translate reporting and analytics requirements into technical specifications. Required Skills & Qualifications: Snowflake (data modeling, performance tuning, access control, external tables, streams & tasks) Apache Airflow (DAG design, task dependencies, dynamic tasks, error handling) dbt (Data Build Tool) (modular SQL development, jinja templating, testing, documentation) Proficiency in SQL, Spark and Python Experience building data pipelines on cloud platforms like AWS, GCP, or Azure Strong knowledge of data warehousing concepts and ELT best practices Familiarity with version control systems (e.g., Git) and CI/CD practices Familiarity with infrastructure-as-code tools like Terraform for provisioning Snowflake or Airflow environments. Excellent problem-solving skills and the ability to work independently. Perks: Flexible Timings 5 Days Working Healthy Environment Celebration Learn and Grow Build the Community Medical Insurance Benefit

Key Responsibilities Develop and maintain data pipelines and ETL processes using Snowflake, Streams & Tasks, and Snowpipe. Leverage Snowpark to build scalable data transformations in Python. Implement Secure Data Sharing, Row-Level Security, and Dynamic Data Masking for governed data access. Create and manage materialized views, automatic clustering, and search optimization for performance tuning. Collaborate with data scientists, analysts, and DevOps teams to deliver end-to-end data solutions. Monitor query performance, troubleshoot issues, and recommend optimizations using Query Profile and Resource Monitors. ________________________________________ Required Technical Skills Strong expertise in Snowflake SQL and data modeling (Star/Snowflake schema). Hands-on with Snowpark, Streams/Tasks, and Secure Data Sharing. Proficiency in Python or Java for data processing with Snowpark. Experience with cloud platforms: AWS, Azure, or GCP (Snowflake hosted environments). Familiarity with CI/CD, Git, and orchestration tools (e.g., Airflow, DBT). Working knowledge of data governance, data security, and compliance best practices. ________________________________________ Qualifications Bachelors or Masters degree in Computer Science, Information Systems, or a related field. Snowflake certification is a strong plus (e.g., SnowPro Core or Advanced). Show more Show less

Key Responsibilities Develop and maintain data pipelines and ETL processes using Snowflake, Streams & Tasks, and Snowpipe. Leverage Snowpark to build scalable data transformations in Python. Implement Secure Data Sharing, Row-Level Security, and Dynamic Data Masking for governed data access. Create and manage materialized views, automatic clustering, and search optimization for performance tuning. Collaborate with data scientists, analysts, and DevOps teams to deliver end-to-end data solutions. Monitor query performance, troubleshoot issues, and recommend optimizations using Query Profile and Resource Monitors. ________________________________________ Required Technical Skills Strong expertise in Snowflake SQL and data modeling (Star/Snowflake schema). Hands-on with Snowpark, Streams/Tasks, and Secure Data Sharing. Proficiency in Python or Java for data processing with Snowpark. Experience with cloud platforms: AWS, Azure, or GCP (Snowflake hosted environments). Familiarity with CI/CD, Git, and orchestration tools (e.g., Airflow, DBT). Working knowledge of data governance, data security, and compliance best practices. ________________________________________ Qualifications Bachelors or Masters degree in Computer Science, Information Systems, or a related field. Snowflake certification is a strong plus (e.g., SnowPro Core or Advanced). Show more Show less

Role: Tech Lead – ETL Location: Offshore/India Who are we looking for? We are looking for 10+ Years of Tech Lead – ETL; multi skilled in different technology mentioned below. Tech Stack: Data Integration Talend, EMR, Airflow DataStage Hue Apache TomCat Python Visualization and Reporting Cognos PowerBI Tableau QlikView MicroStrategy Sigma Monitoring/Scheduler Tools App Dynamics Data Power Operational Dashboard (DPOD) Microsoft System Center Orchestrator (IR Batch Scheduler) AutoSys AWS CloudWatch Technical Skills: Strong knowledge with working experience in one from each category mentioned above. Key Responsibilities: Should have knowledge in extracting data from heterogeneous sources such as databases, CRM, flat files, etc. Create and design the ETL processes and Pipelines Ensure Data quality, modeling and tuning Strong troubleshooting and Problem Solving skills to identify the issues quickly; provide innovative tools for that. Collaboration: Working with developers, other administrators, and stakeholders to ensure smooth operations and integration. Continuous Improvement: Staying up to date with the latest industry trends and technologies to drive continuous improvement and innovation. DevOps and Agile Practices: Aligning middleware operations with DevOps and Agile principles and contributing to automation of middleware-related tasks. Qualification: · Education qualification: Any Graduate Show more Show less

Ready to shape the future of work? At Genpact, we don’t just adapt to change—we drive it. AI and digital innovation are redefining industries, and we’re leading the charge. Genpact’s AI Gigafactory , our industry-first accelerator, is an example of how we’re scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI , our breakthrough solutions tackle companies’ most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that’s shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions – we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn , X , YouTube , and Facebook . Inviting applications for the role of Principal Consultant- Sr. Snowflake Data Engineer ( Snowflake+ Python+Cloud ) ! In this role, the Sr. Snowflake Data Engineer is responsible for providing technical direction and lead a group of one or more developer to address a goal. Job Description : E xperience in IT industry W orking experience with building productionized data ingestion and processing data pipelines in Snowflake Strong understanding on Snowflake Architecture Fully well-versed with data warehousing concepts. Expertise and excellent understanding of Snowflake features and integration of Snowflake with other data processing. Able to create the data pipeline for ETL /ELT Good to have DBT experience Excellent presentation and communication skills, both written and verbal Ability to problem solve and architect in an environment with unclear requirements. Able to create the high level and low-level design document based on requirement. Hands on experience in configuration, troubleshooting, testing and managing data platforms, on premises or in the cloud. Awareness on data visualisation tools and methodologies Work independently on business problems and generate meaningful insights Good to have some experience/knowledge on Snowpark or Streamlit or GenAI but not mandatory. Should have experience on implementing Snowflake Best Practices Snowflake SnowPro Core Certification will be add ed an advantage Roles and Responsibilities : Requirement gathering, creating design document, providing solutions to customer, work with offshore team etc. Writing SQL queries against Snowflake , developing scripts to do Extract, Load, and Transform data. Hands-on experience with Snowflake utilities such as SnowSQL , Bulk copy, Snow p ipe , Tasks, Streams, Time travel, Cloning, Optimizer, Metadata Manager, data sharing, stored procedures and UDFs , Snowsight . Have experience with Snowflake cloud data warehouse and AWS S3 bucket or Azure blob storage container for integrating data from multiple source system . Should have have some exp on AWS services (S3, Glue, Lambda) or Azure services ( Blob Storage, ADLS gen2, ADF) Should have good experience in Python / Pyspark . integration with Snowflake and cloud (AWS/Azure) with ability to leverage cloud services for data processing and storage. Proficiency in Python programming language, including knowledge of data types, variables, functions, loops, conditionals, and other Python-specific concepts. Knowledge of ETL (Extract, Transform, Load) processes and tools, and ability to design and develop efficient ETL jobs using Python and Pyspark . Should have some experience on Snowflake RBAC and data security . Should have good experience in implementing CDC or SCD type - 2 . Should have good experience in implementing Snowflake Best Practices In-depth understanding of Data Warehouse, ETL concepts and Data Modelling Experience in requirement gathering, analys is, designing, development, and deployment . Should Have experience building data ingestion pipeline Optimize and tune data pipelines for performance and scalability Able to communicate with clients and lead team. Proficiency in working with Airflow or other workflow management tools for scheduling and managing ETL jobs. Good to have experience in deployment using CI/CD tools and exp in repositories like Azure repo , Github etc. Qualifications we seek in you! Minimum qualifications B.E./ Masters in Computer Science , Information technology, or Computer engineering or any equivalent degree with good IT experience and relevant as Senior Snowflake Data Engineer . Skill Metrix: Snowflake, Python/ PySpark , AWS/Azure, ETL concepts, Data Modeling & Data Warehousing concepts Why join Genpact? Be a transformation leader – Work at the cutting edge of AI, automation, and digital innovation Make an impact – Drive change for global enterprises and solve business challenges that matter Accelerate your career – Get hands-on experience, mentorship, and continuous learning opportunities Work with the best – Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture – Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let’s build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training. Job Principal Consultant Primary Location India-Kolkata Schedule Full-time Education Level Bachelor's / Graduation / Equivalent Job Posting Jun 15, 2025, 11:17:34 PM Unposting Date Ongoing Master Skills List Digital Job Category Full Time

Job Description Global Data Insight & Analytics organization is looking for a top-notch Software Engineer who has also got Machine Learning knowledge & Experience to add to our team to drive the next generation of AI/ML (Mach1ML) platform. In this role you will work in a small, cross-functional team. The position will collaborate directly and continuously with other engineers, business partners, product managers and designers from distributed locations, and will release early and often. The team you will be working on is focused on building Mach1ML platform – an AI/ML enablement platform to democratize Machine Learning across Ford enterprise (like OpenAI’s GPT, Facebook’s FBLearner, etc.) to deliver next-gen analytics innovation. We strongly believe that data has the power to help create great products and experiences which delight our customers. We believe that actionable and persistent insights, based on high quality data platform, help business and engineering make more impactful decisions. Our ambitions reach well beyond existing solutions, and we are in search of innovative individuals to join this Agile team. This is an exciting, fast-paced role which requires outstanding technical and organization skills combined with critical thinking, problem-solving and agile management tools to support team success. Responsibilities What you'll be able to do: As a Software Engineer, you will work on developing features for Mach1ML platform, support customers in model deployment using Mach1ML platform on GCP and On-prem. You will follow Rally to manage your work. You will incorporate an understanding of product functionality and customer perspective for model deployment. You will work on the cutting-edge technologies such as GCP, Kubernetes, Docker, Seldon, Tekton, Airflow, Rally, etc. Position Responsibilities: Work closely with Tech Anchor, Product Manager and Product Owner to deliver machine learning use cases using Ford Agile Framework. Work with Data Scientists and ML engineers to tackle challenging AI problems. Work specifically on the Deploy team to drive model deployment and AI/ML adoption with other internal and external systems. Help innovate by researching state-of-the-art deployment tools and share knowledge with the team. Lead by example in use of Paired Programming for cross training/upskilling, problem solving, and speed to delivery. Leverage latest GCP, CICD, ML technologies Critical Thinking: Able to influence the strategic direction of the company by finding opportunities in large, rich data sets and crafting and implementing data driven strategies that fuel growth including cost savings, revenue, and profit. Modelling: Assessments, and evaluating impacts of missing/unusable data, design and select features, develop, and implement statistical/predictive models using advanced algorithms on diverse sources of data and testing and validation of models, such as forecasting, natural language processing, pattern recognition, machine vision, supervised and unsupervised classification, decision trees, neural networks, etc. Analytics: Leverage rigorous analytical and statistical techniques to identify trends and relationships between different components of data, draw appropriate conclusions and translate analytical findings and recommendations into business strategies or engineering decisions - with statistical confidence Data Engineering: Experience with crafting ETL processes to source and link data in preparation for Model/Algorithm development. This includes domain expertise of data sets in the environment, third-party data evaluations, data quality Visualization: Build visualizations to connect disparate data, find patterns and tell engaging stories. This includes both scientific visualization as well as geographic using applications such as Seaborn, Qlik Sense/PowerBI/Tableau/Looker Studio, etc. Qualifications Minimum Requirements we seek: Bachelor’s or master’s degree in computer science engineering or related field or a combination of education and equivalent experience. 3+ years of experience in full stack software development 3+ years’ experience in Cloud technologies & services, preferably GCP 3+ years of experience of practicing statistical methods and their accurate application e.g. ANOVA, principal component analysis, correspondence analysis, k-means clustering, factor analysis, multi-variate analysis, Neural Networks, causal inference, Gaussian regression, etc. 3+ years’ experience with Python, SQL, BQ. Experience in SonarQube, CICD, Tekton, terraform, GCS, GCP Looker, Google cloud build, cloud run, Vertex AI, Airflow, TensorFlow, etc., Experience in Train, Build and Deploy ML, DL Models Experience in HuggingFace, Chainlit, Streamlit, React Ability to understand technical, functional, non-functional, security aspects of business requirements and delivering them end-to-end. Ability to adapt quickly with opensource products & tools to integrate with ML Platforms Building and deploying Models (Scikit learn, DataRobots, TensorFlow PyTorch, etc.) Developing and deploying On-Prem & Cloud environments Kubernetes, Tekton, OpenShift, Terraform, Vertex AI Our Preferred Requirements: Master’s degree in computer science engineering, or related field or a combination of education and equivalent experience. Demonstrated successful application of analytical methods and machine learning techniques with measurable impact on product/design/business/strategy. Proficiency in programming languages such as Python with a strong emphasis on machine learning libraries, generative AI frameworks, and monitoring tools. Utilize tools and technologies such as TensorFlow, PyTorch, scikit-learn, and other machine learning libraries to build and deploy machine learning solutions on cloud platforms. Design and implement cloud infrastructure using technologies such as Kubernetes, Terraform, and Tekton to support scalable and reliable deployment of machine learning models, generative AI models, and applications. Integrate machine learning and generative AI models into production systems on cloud platforms such as Google Cloud Platform (GCP) and ensure scalability, performance, and proactive monitoring. Implement monitoring solutions to track the performance, health, and security of systems and applications, utilizing tools such as Prometheus, Grafana, and other relevant monitoring tools. Conduct code reviews and provide constructive feedback to team members on machine learning-related projects. Knowledge and experience in agentic workflow based application development and DevOps Stay up to date with the latest trends and advancements in machine learning and data science. Show more Show less

You are passionate about quality and how customers experience the products you test. You have the ability to create, maintain and execute test plans in order to verify requirements. As a Quality Engineer at Equifax, you will be a catalyst in both the development and the testing of high priority initiatives. You will develop and test new products to support technology operations while maintaining exemplary standards. As a collaborative member of the team, you will deliver QA services (code quality, testing services, performance engineering, development collaboration and continuous integration). You will conduct quality control tests in order to ensure full compliance with specified standards and end user requirements. You will execute tests using established plans and scripts; documents problems in an issues log and retest to ensure problems are resolved. You will create test files to thoroughly test program logic and verify system flow. You will identify, recommend and implement changes to enhance effectiveness of QA strategies. What You Will Do Independently develop scalable and reliable automated tests and frameworks for testing software solutions. Specify and automate test scenarios and test data for a highly complex business by analyzing integration points, data flows, personas, authorization schemes and environments Develop regression suites, develop automation scenarios, and move automation to an agile continuous testing model. Pro-actively and collaboratively taking part in all testing related activities while establishing partnerships with key stakeholders in Product, Development/Engineering, and Technology Operations. What Experience You Need Bachelor's degree in a STEM major or equivalent experience 5-7 years of software testing experience Able to create and review test automation according to specifications Ability to write, debug, and troubleshoot code in Java, Springboot, TypeScript/JavaScript, HTML, CSS Creation and use of big data processing solutions using Dataflow/Apache Beam, Bigtable, BigQuery, PubSub, GCS, Composer/Airflow, and others with respect to software validation Created test strategies and plans Led complex testing efforts or projects Participated in Sprint Planning as the Test Lead Collaborated with Product Owners, SREs, Technical Architects to define testing strategies and plans. Design and development of micro services using Java, Springboot, GCP SDKs, GKE/Kubeneties Deploy and release software using Jenkins CI/CD pipelines, understand infrastructure-as-code concepts, Helm Charts, and Terraform constructs Cloud Certification Strongly Preferred What Could Set You Apart An ability to demonstrate successful performance of our Success Profile skills, including: Attention to Detail - Define test case candidates for automation that are outside of product specifications. i.e. Negative Testing; Create thorough and accurate documentation of all work including status updates to summarize project highlights; validating that processes operate properly and conform to standards Automation - Automate defined test cases and test suites per project Collaboration - Collaborate with Product Owners and development team to plan and and assist with user acceptance testing; Collaborate with product owners, development leads and architects on functional and non-functional test strategies and plans Execution - Develop scalable and reliable automated tests; Develop performance testing scripts to assure products are adhering to the documented SLO/SLI/SLAs; Specify the need for Test Data types for automated testing; Create automated tests and tests data for projects; Develop automated regression suites; Integrate automated regression tests into the CI/CD pipeline; Work with teams on E2E testing strategies and plans against multiple product integration points Quality Control - Perform defect analysis, in-depth technical root cause analysis, identifying trends and recommendations to resolve complex functional issues and process improvements; Analyzes results of functional and non-functional tests and make recommendation for improvements; Performance / Resilience: Understanding application and network architecture as inputs to create performance and resilience test strategies and plans for each product and platform. Conducting the performance and resilience testing to ensure the products meet SLAs / SLOs Quality Focus - Review test cases for complete functional coverage; Review quality section of Production Readiness Review for completeness; Recommend changes to existing testing methodologies for effectiveness and efficiency of product validation; Ensure communications are thorough and accurate for all work documentation including status and project updates Risk Mitigation - Work with Product Owners, QE and development team leads to track and determine prioritization of defects fixes Show more Show less

Designation: Solution Architect Office Location: Gurgaon Position Description: As a Solution Architect, you will be responsible for leading the development and delivery of the platforms. This includes overseeing the entire product lifecycle from the solution until execution and launch, building the right team & close collaboration with business and product teams. Primary Responsibilities: Design end-to-end solutions that meet business requirements and align with the enterprise architecture. Define the architecture blueprint, including integration, data flow, application, and infrastructure components. Evaluate and select appropriate technology stacks, tools, and frameworks. Ensure proposed solutions are scalable, maintainable, and secure. Collaborate with business and technical stakeholders to gather requirements and clarify objectives. Act as a bridge between business problems and technology solutions. Guide development teams during the execution phase to ensure solutions are implemented according to design. Identify and mitigate architectural risks and issues. Ensure compliance with architecture principles, standards, policies, and best practices. Document architectures, designs, and implementation decisions clearly and thoroughly. Identify opportunities for innovation and efficiency within existing and upcoming solutions. Conduct regular performance and code reviews, and provide feedback to the development team members to improve professional development. Lead proof-of-concept initiatives to evaluate new technologies. Functional Responsibilities: Facilitate daily stand-up meetings, sprint planning, sprint review, and retrospective meetings. Work closely with the product owner to priorities the product backlog and ensure that user stories are well-defined and ready for development. Identify and address issues or conflicts that may impact project delivery or team morale. Experience with Agile project management tools such as Jira and Trello. Required Skills: Bachelor's degree in Computer Science, Engineering, or related field. 7+ years of experience in software engineering, with at least 3 years in a solution architecture or technical leadership role. Proficiency with AWS or GCP cloud platform. Strong implementation knowledge in JS tech stack, NodeJS, ReactJS, Experience with JS stack - ReactJS, NodeJS. Experience with Database Engines - MySQL and PostgreSQL with proven knowledge of Database migrations, high throughput and low latency use cases. Experience with key-value stores like Redis, MongoDB and similar. Preferred knowledge of distributed technologies - Kafka, Spark, Trino or similar with proven experience in event-driven data pipelines. Proven experience with setting up big data pipelines to handle high volume transactions and transformations. Experience with BI tools - Looker, PowerBI, Metabase or similar. Experience with Data warehouses like BigQuery, Redshift, or similar. Familiarity with CI/CD pipelines, containerization (Docker/Kubernetes), and IaC (Terraform/CloudFormation). Good to Have: Certifications such as AWS Certified Solutions Architect, Azure Solutions Architect Expert, TOGAF, etc. Experience setting up analytical pipelines using BI tools (Looker, PowerBI, Metabase or similar) and low-level Python tools like Pandas, Numpy, PyArrow Experience with data transformation tools like DBT, SQLMesh or similar. Experience with data orchestration tools like Apache Airflow, Kestra or similar. Work Environment Details: About Affle: Affle is a global technology company with a proprietary consumer intelligence platform that delivers consumer engagement, acquisitions, and transactions through relevant Mobile Advertising. The platform aims to enhance returns on marketing investment through contextual mobile ads and also by reducing digital ad fraud. While Affle's Consumer platform is used by online & offline companies for measurable mobile advertising, its Enterprise platform helps offline companies to go online through platform-based app development, enablement of O2O commerce and through its customer data platform. Affle India successfully completed its IPO in India on 08. Aug.2019 and now trades on the stock exchanges (BSE: 542752 & NSE:AFFLE). Affle Holdings is the Singapore based promoter for Affle India and its investors include Microsoft, Bennett Coleman &Company (BCCL) amongst others. For more details: www.affle.com About BU : Ultra - Access deals, coupons, and walled gardens based user acquisition on a single platform to offer bottom-funnel optimization across multiple inventory sources. For more details, please visit: https://www.ultraplatform.io/ Show more Show less

Job Overview: The person will be responsible for expanding and optimizing our data and data pipeline architecture. The ideal candidate is an experienced data pipeline builder who enjoys optimizing data systems and building them from the ground up. You’ll be Responsible for ? Create and maintain optimal data pipeline architecture, assemble large, complex data sets that meet functional / non-functional business requirements. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Cloud technologies. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to strive for greater functionality in our data systems. You’d have? We are looking for a candidate with 3+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools: Experience with data pipeline and workflow management tools: Apache Airflow, NiFi, Talend etc. • Experience with relational SQL and NoSQL databases, including Clickhouse, Postgres and MySQL. Experience with stream-processing systems: Storm, Spark-Streaming, Kafka etc. Experience with object-oriented/object function scripting languages: Python, Scala, etc. Experience building and optimizing data pipelines, architectures and data sets. Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. Strong analytic skills related to working with unstructured datasets. Build processes supporting data transformation, data structures, metadata, dependency and workload management. Working knowledge of message queuing, stream processing, and highly scalable data stores Why Join us? Impactful Work: Play a pivotal role in safeguarding Tanla's assets, data, and reputation in the industry. Tremendous Growth Opportunities: Be part of a rapidly growing company in the telecom and CPaaS space, with opportunities for professional development. Innovative Environment: Work alongside a world-class team in a challenging and fun environment, where innovation is celebrated. Tanla is an equal opportunity employer. We champion diversity and are committed to creating an inclusive environment for all employees. www.tanla.com Show more Show less

Job Summary: We are seeking a skilled Database & ETL Developer with strong expertise in SQL, data modeling, cloud integration, and reporting tools. The ideal candidate will be responsible for designing scalable database architectures, optimizing complex queries, working with modern ETL tools, and delivering insightful dashboards and reports. This role requires collaboration across multiple teams and the ability to manage tasks in a dynamic, agile environment. Experience: 7+ Years Location: Mohali (Work from Office Only) Key Responsibilities: Design and implement normalized and scalable database schemas using ER modeling techniques. Develop, maintain, and optimize stored procedures, triggers, views, and advanced SQL queries (e.g., joins, subqueries, indexing). Execute database backup, restore, and recovery operations ensuring data integrity and high availability. Optimize SQL performance through indexing strategies, execution plans, and query refactoring. Lead and support cloud migration and integration projects involving platforms such as AWS and Azure. Implement and manage data lake architectures such as AWS HealthLake and AWS Glue pipelines. Create and manage interactive dashboards and business reports using Power BI, Amazon QuickSight, or Tableau. Collaborate with cross-functional teams and use tools like JIRA, Azure Boards, ClickUp, or Trello for task and project tracking. Required Skills: Strong experience with SQL Server or PostgreSQL , including advanced T-SQL programming. In-depth knowledge of ER modeling and relational database design principles. Proficiency in query optimization , indexing, joins, and subqueries. Hands-on experience with modern ETL and data integration platforms such as Airbyte, Apache Airflow, Azure Data Factory (ADF), and AWS Glue . Understanding of Data Lake / Health Lake architectures and their role in cloud data ecosystems. Proficiency with reporting tools like Power BI, Amazon QuickSight, or Tableau . Experience with database backup, restore , and high availability strategies . Familiarity with project/task tracking tools such as JIRA, Azure Boards, ClickUp, or Trello . Soft Skills: Strong verbal and written communication skills. Excellent problem-solving and troubleshooting abilities. Self-motivated with the ability to manage priorities and work independently across multiple projects. Nice to Have: Certification in cloud platforms (AWS, Azure). Exposure to healthcare data standards and compliance (e.g., HIPAA, FHIR). Company overview: smartData is a leader in global software business space when it comes to business consulting and technology integrations making business easier, accessible, secure and meaningful for its target segment of startups to small & medium enterprises. As your technology partner, we provide both domain and technology consulting and our inhouse products and our unique productized service approach helps us to act as business integrators saving substantial time to market for our esteemed customers. With 8000+ projects, vast experience of 20+ years, backed by offices in the US, Australia, and India, providing next door assistance and round-the-clock connectivity, we ensure continual business growth for all our customers. Our business consulting and integrator services via software solutions focus on important industries of healthcare, B2B, B2C, & B2B2C platforms, online delivery services, video platform services, and IT services. Strong expertise in Microsoft, LAMP stack, MEAN/MERN stack with mobility first approach via native (iOS, Android, Tizen) or hybrid (React Native, Flutter, Ionic, Cordova, PhoneGap) mobility stack mixed with AI & ML help us to deliver on the ongoing needs of customers continuously. For more information, visit http://www.smartdatainc.com 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

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

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

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

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

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

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

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

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

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

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

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

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

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

Responsibilities Role description Design, develop, and implement solutions using Oracle BRM 12 (or above), Java Spring Boot, and related technologies. Customize and extend BRM functionality through opcode development and configuration. Develop and maintain integrations between BRM and other systems using APIs and messaging queues. Troubleshoot and resolve complex issues related to BRM, Java applications, and system integrations. Write efficient database queries and shell scripts for automation and data analysis. Work with cloud technologies (e.g., AWS, GCP, Azure) to deploy and manage applications. Utilize and manage data in various databases (Oracle, DynamoDB, NoSQL). Integrate with messaging queues (Kafka, AWS SQS). Contribute to the design and implementation of microservices. Monitor application performance and identify areas for optimization. Participate in code reviews and provide constructive feedback. Collaborate effectively with other developers, testers, and business stakeholders. Provide support during US business hours for a few hours. Must-Have Skills Oracle BRM 12 (or above): Experience with opcode customization and configuration. Java Development: Proficiency in Java, with hands-on experience using Spring Boot. Database Queries: Strong experience with SQL, PL/SQL, and shell scripting for automation and data analysis. Cloud Technologies: Hands-on experience with at least one of the major cloud platforms (AWS, GCP, Azure). Messaging Systems: Experience with systems like Kafka and AWS SQS. Microservices: Understanding of microservice design patterns and their implementation. Debugging & Troubleshooting: Excellent debugging skills and problem-solving ability. Communication: Strong written and verbal communication skills to work with diverse teams. Good-to-Have Skills Monitoring Tools: Familiarity with tools like Chaossearch, Kibana, Grafana, Datadog. Containerization: Experience with Docker and Kubernetes. Apache Airflow: Experience with workflow orchestration. Additional Cloud Platforms: Knowledge of other cloud platforms beyond AWS, GCP, or Azure. Experience Range 5+ years of hands-on experience with Oracle BRM, Java Spring Boot, and cloud technologies. Qualifications Education: Bachelor’s degree in Computer Science or a related field. Skills Oracle Brm,Javaspringboot,GCP Show more Show less