Responsibilities:
- Design, develop, and maintain ETL/ELT pipelines using AWS services (Glue, Lambda, Step Functions, Data Pipeline, EMR).
- Build and optimize data lakes and data warehouses using Amazon S3, Redshift, Athena, and Snowflake (if applicable).
- Implement and manage data ingestion frameworks from structured and unstructured data sources (APIs, RDBMS, streaming, etc.).
- Ensure data quality, integrity, and security using tools like AWS Lake Formation, IAM, and KMS.
- Strong proficiency in SQL, Python, and PySpark.
- Expertise in AWS data ecosystem – including Glue, Redshift, S3, Lambda, EMR, and Athena.
Mandatory skill sets:
- Strong proficiency in SQL, Python, and PySpark.
- Expertise in AWS data ecosystem – including Glue, Redshift, S3, Lambda, EMR, and Athena.
Preferred skill sets:
- AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect.
Years of experience required:
6-10
Education qualification:
B.Tech / M.Tech / MBA / MCA
