Looking for a hands‑on AWS Technical Lead – Data Engineering with 6 to 10 years of total experience to design and deliver scalable, secure, and high‑performance data platforms on AWS.
This role focuses on strong individual contribution with technical ownership, working closely with global teams, architects, and clients to deliver enterprise‑grade data engineering solutions. The position requires deep expertise in AWS data services, SQL, and Python, and the ability to build and optimize reliable data pipelines for analytics and business use cases.

Job Description:

Min. 6 and max upto 10.

Must Have Skills
 

'Cloud & Data Engineering (AWS)Strong hands‑on experience with AWS data services, including:Amazon S3, AWS Glue, Athena, RedshiftExperience designing cloud‑native data lakes and data warehouse architectures on AWSDeep understanding of batch and streaming data pipelinesExperience building scalable, fault‑tolerant data ingestion and transformation workflowsSQL & Python (Mandatory)Strong SQL expertiseWriting complex SQL for transformations, aggregations, performance tuning, and analyticsHands‑on experience handling large‑scale datasets in Redshift / AthenaStrong Python programming skills (mandatory) for data engineering use casesPySpark / Spark‑based processingBuilding reusable ETL components, utilities, and data pipelinesStrong understanding of data modeling, transformations, and performance optimizationData Processing & EngineeringProven hands‑on experience with distributed processing frameworks such as Spark / PySparkExperience working with structured, semi‑structured, and unstructured dataSolid understanding of schema design, partitioning, and query optimizationDevOps & Platform EngineeringExperience with Infrastructure as Code using Terraform and/or CloudFormationHands‑on experience building and maintaining CI/CD pipelines for data platformsExposure to containerized workloads (Docker, ECS/EKS where applicable to data workloads)Collaboration & OwnershipStrong ownership mindset for solution quality, performance, and production stabilityExcellent communication skills to collaborate with architects, DevOps, QA, and business stakeholders

Good to Have

Experience with real‑time/streaming technologies (Kinesis, Kafka, MSK)Exposure to Lakehouse architectures and modern data platform patternsExperience integrating AWS data platforms with BI and analytics toolsKnowledge of data governance, data quality, and metadata managementFamiliarity with FinOps practices for optimizing AWS data platform costsExposure to marketing, customer, or analytics data domains (CDP / MarTech)Experience working in Agile delivery models with global delivery exposure

Key ResponsibilitiesData Platform Design & DevelopmentDesign and implement AWS‑based data engineering solutions aligned to enterprise standardsBuild and optimize batch and streaming data pipelines using AWS native and open‑source toolsDevelop SQL‑driven transformations and Python‑based data pipelines for analytics use casesDesign efficient data models for performance, scalability, and cost effectivenessDelivery & Quality OwnershipOwn data engineering deliverables from development through production supportPerform performance tuning, cost optimization, and capacity planningTroubleshoot complex data pipeline and production issues, including root‑cause analysisEnsure solutions meet requirements for security, reliability, and scalabilityCollaboration & Client EngagementWork closely with architects, product owners, and client stakeholdersTranslate business and analytics requirements into robust AWS data engineering solutionsProvide clear technical inputs, estimates, and implementation trade‑offsContribute to solution discussions and technical design reviewsEngineering Best PracticesFollow and contribute to coding standards, documentation, and data engineering best practicesParticipate in code reviews and continuous improvement initiativesEnsure adherence to AWS, security, and compliance guidelines

Location:

DGS India - Pune - Indiqube Orchid

Brand:

Merkle

Time Type:

Full time

Contract Type:

Permanent