Looking for a hands‑on Senior Data Engineer – AWS with experience to development, build, and maintain scalable, secure, and high‑performance data platforms on AWS.

This is an individual contributor role focused on data pipeline development, cloud data engineering, and analytics enablement. The role requires strong hands‑on skills in AWS data services, SQL, and Python, along with experience building reliable batch and streaming data pipelines in a global delivery environment.:

Min 3 and max upto 5.

Must Have

'Cloud &

- Data Engineering (AWS)Solid hands‑on experience with AWS data services, including:
- Amazon S3- AWS Glue- Amazon Athena- Amazon Redshift- Amazon EMRExperience designing cloud‑native data lakes and data warehouse architecturesSolid understanding of batch data pipelines and basic exposure to streaming conceptsSQL &
- Python (Mandatory)Strong SQL skills (mandatory)Writing complex queries, joins, aggregations, and transformationsExperience working with large datasets in Redshift / AthenaStrong Python skills (mandatory)Python for data engineering and ETL use casesExperience with PySpark / Spark is a strong plusGood understanding of data modeling, transformations, and performance tuningData Processing &
- EngineeringHands‑on experience with distributed data processing frameworks (Spark / PySpark)Experience handling structured and semi‑structured dataUnderstanding of schema evolution, data quality checks, and validation logicDevOps &




- Platform BasicsWorking knowledge of Infrastructure as Code (Terraform and/or CloudFormation)Basic experience with CI/CD pipelines for data workloadsUnderstanding of logging and monitoring using CloudWatchCollaborationAbility to work closely with architects, DevOps, QA, and business stakeholdersGood communication skills to explain technical concepts clearlyGood to HaveExposure to streaming technologies such as Amazon Kinesis or KafkaFamiliarity with Lakehouse and modern data platform patternsExperience integrating AWS data platforms with BI / reporting toolsBasic knowledge of data governance, data quality, and metadata conceptsAwareness of AWS cost optimization best practicesExperience working in Agile delivery models, with global clientsExposure to AI / ML

Key ResponsibilitiesData Engineering & DevelopmentDesign and build scalable ETL / ELT pipelines on AWSDevelop SQL‑based data transformations and Python‑based data pipelinesImplement data ingestion pipelines using AWS services such as S3, Glue, EMRBuild data models optimized for analytics, performance, and cost efficiencyPlatform & OperationsSupport deployment and execution of data pipelines across environmentsMonitor pipeline performance, reliability, and data qualityTroubleshoot data pipeline issues and perform root‑cause analysisApply best practices for security, reliability, and scalabilityCollaboration & DeliveryWork closely with architects and product teams to understand requirementsTranslate business and analytics needs into working AWS data solutionsContribute to documentation, code reviews, and engineering standardsLocation:

DGS India - Pune - Indiqube OrchidBrand:

MerkleTime Type:

Full timeContract Type:

Permanent

📌 Data Engineer (Pune)
🏢 dentsu
📍 Pune