AWS Data Engineer Lead

Job Title:Data Engineer

Primary Skill: AWS, DynamoDB, Aurora PostgreSQL, AWS Sagemaker, Spark, Scala/Python,Medallion Architecture

Location: Hyderabad/ Pune/ Coimbatore

Experience: 3 -9 years of experience

Mode of working - 5 Daya work from office

We are looking for an experienced AWS Data Engineer with strong hands‑on expertise in building scalable, reliable data pipelines in a Lakehouse/Medallion architecture. The ideal candidate will have deep knowledge of Spark/PySpark, Terraform, and modern data engineering patterns.

Key Responsibilities

• Build and operate data pipelines using PySpark/Spark, SQL, and AWS services.
• Implement Medallion (Bronze/Silver/Gold) architecture with proper separation of concerns.
• Design incremental processing, SCD Type 2, CDC/merge, and late-arriving/out‑of‑sequence data handling.
• Ensure pipelines are idempotent, resilient, and re‑processable.
• Manage AWS data infrastructure using Terraform.
• Apply strong data quality, deduplication, schema validation, and operational best practices.

Required Skills

• Terraform for AWS infrastructure provisioning
• PySpark/Spark, Python, Advanced SQL
• Lakehouse/Medallion Architecture (Bronze/Silver/Gold)
• Type 2 Dimensions, CDC/Merge processing
• Incremental & historical processing, deduplication, late-arriving data handling
• Idempotency and resilient pipeline patterns
• AWS data services (S3, Glue, EMR, Lambda, Step Functions, etc.)
• Data modeling fundamentals & data quality mindset

Candidates Must Be Able to Explain

• Updates/deletes from relational sources
• Deterministic deduplication
• Late-arriving/out-of-sequence data handling
• Idempotent pipeline design
• Merge keys, ordering columns, event time vs ingest time, soft deletes, reprocessing windows

If you are interested in the above role, kindly fill in the details below and share your updated resume here.

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