Key Responsibilities

Design, develop, and maintain end-to-end data engineering pipelines on AWS

Build and optimize ETL/ELT pipelines using Python and PySpark

Work with structured and semi-structured data using SQL

Ingest data from multiple sources (APIs, databases, streaming, files)

Perform data cleaning, transformation, and validation

Implement data quality checks and monitoring

Optimize data processing for performance and cost

Collaborate with data scientists, analysts, and stakeholders

Support the entire data engineering lifecycle: ingestion processing storage analytics

Mandatory Technical Skills

AWS: S3, Glue, EMR, Lambda, Redshift, Athena (mandatory)

Programming: Python, PySpark

Databases: Strong SQL (PostgreSQL / MySQL / Redshift)

Data Processing: Batch and streaming data pipelines

ETL Tools: AWS Glue / Spark-based frameworks

Good to Have

Experience with Airflow or AWS Step Functions

Knowledge of Delta Lake / Iceberg / Hudi

Exposure to CI/CD for data pipelines

Experience with data warehousing and analytics

Education

B.E / B.Tech / M.Tech / MCA or equivalent

Senior AWS Data engineer