AWS Data Engineer - ETL/PySpark/Python (5-12 yrs)

Position : AWS Data Engineer

Experience : 5+ Yrs

Location : Bangalore, Hyderabad, Chennai, Pune, Gurgaon

Overview :

We are seeking experienced AWS Data Engineers to join our data engineering team and play a pivotal role in designing, building, and maintaining scalable, secure, and high-performance data pipelines on AWS. The ideal candidate will have deep expertise in AWS native services, PySpark-based data processing, and modern data architecture.

Key Responsibilities :

- Design, build, and optimize scalable ETL/ELT pipelines using AWS Glue, PySpark, and Step Functions.

- Work with structured and semi-structured data in S3, Athena, and Lake Formation for efficient querying and secure access.

- Develop serverless data processing solutions using AWS Lambda, integrated with orchestration tools.

- Write and optimize advanced SQL and PL/SQL scripts for data transformation and analytics.

- Architect and maintain data lakes and data warehouses using S3, Aurora, and Athena.

- Implement robust data governance, metadata management, lineage tracking, and access controls via Lake Formation, CloudFront, EBS/EFS, and IAM.

- Engage in data modeling for both OLTP and OLAP systems.

- Collaborate with data scientists, analysts, and business teams to translate business requirements into data solutions.

- Monitor, troubleshoot, and improve the performance, scalability, and reliability of data pipelines.

Required Skills & Expertise :

Core Technologies :

- AWS Services: Glue, Athena, Step Functions, Lambda, Lake Formation, S3, EC2, Aurora, EBS/EFS, CloudFront

- BIg Query / GCP

- Languages/Frameworks: Python, PySpark, SQL, PL/SQL

- Data Engineering Concepts:

- ETL/ELT Fundamentals

- Data Warehousing

- Data Lakes

- Modern Data Platform Architecture

- Metadata & Lineage Management