AWS Data Engineer

We AreWe are At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. With top clients to boast about, Synechron has a global workforce of 14,500+, and has 58 offices in 21 countries within key global markets.

Role ResponsibilitiesDesigning, building, and delivering optimised enterprise-wide data ingestion, data integration solutions for Cloud-based, Big Data and Data warehouse platforms with comprehensive test coverageBuilding group data products, by integrating large sets of data derived from internal and external sources and publishing them for downstream consumption (eg File, Reporting Tools, Events, etc.Defining and implementing test cases, test strategy, test plans for bigdata/ cloud applications and pipelinesEnd-to-end testing of ETL process, data lakes and test data preparation/ creation, validating data accuracy, completeness, transformation logic, data quality and perform

Skills Require
Experience in building data solution in Hadoop and BigData platforms, using Spark framework, Ab Initio and Python.Experience with AWS Technologies including Redshift, Iceberg tables, EMR, Glue, Athena,S3.Data Analysis: Expertise in using tools like Zepplin, AlationHub Data Processing: Strong expertise in Python, SQL, Spark Data Governance & Security: Experience with AWS DataZone, Lake Formation, IAM, encryption.Marketplace & APIs: Exposure to AWS Marketplace, API Gateway, and data monetization strategies.Automation & CI/CD: Experience with CloudFormation, GitOps, and serverless frameworks.Experience is using test management tools like JIRA, version controlGitPerformance Optimization: Ability to fine-tune ETL jobs, query performance, and cost efficiencies.