Job Title:AWS Data Engineer Lead

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

Location: Hyderabad/ Pune/ Coimbatore

Experience: 7-10 years of experience

Mode of working - 4 Days work from office

We are looking for an experienced AWS Data Engineer with strong handson expertise in building scalable, reliable data pipelines in a Lakehouse/Medallion architecture. The ideal candidate will have deep knowledge of Spark/PySpark, Terraform, and up-to-date 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/outofsequence data handling.
- Ensure pipelines are idempotent, resilient, and reprocessable.
- 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

📌 AWS Data Engineer Lead (Hyderabad)
🏢 ValueMomentum
📍 Hyderabad