AWS Data Engineer - ETL (5-10 yrs)

Job Description :

We are looking for a highly skilled AWS Data Engineer with expertise in PySpark, AWS Glue, EMR, Lambda, DMS, and ETL pipelines. The ideal candidate should have hands-on experience in designing, implementing, and optimizing data pipelines on AWS while ensuring scalability and performance.

Key Responsibilities :

- Design and develop scalable ETL pipelines using AWS Glue, EMR, and PySpark.

- Manage and optimize AWS EMR clusters for big data processing.

- Implement AWS Lambda functions for serverless data processing.

- Work with AWS Database Migration Service (DMS) to migrate data between databases.

- Ensure data security, governance, and compliance with best practices.

- Monitor and optimize ETL performance across AWS services.

- Collaborate with business stakeholders and client management teams to define data requirements.

- Troubleshoot and resolve data processing and pipeline issues.

- Develop automated data validation and monitoring solutions.

- Stay updated with the latest AWS data engineering trends and best practices.

Required Skills & Expertise :

- AWS Glue & EMR - Experience with large-scale ETL data processing

- PySpark - Strong hands-on experience with distributed data processing

- AWS Lambda - Serverless data transformation and event-driven processing

- AWS DMS (Database Migration Service) - Expertise in data migration between relational and NoSQL databases

- ETL Development - Strong experience in building, testing, and deploying ETL pipelines

- Client Management - Ability to work with business stakeholders to define data solutions

- Data Security & Performance Optimization - Ensuring data compliance and efficiency

- Strong Problem-Solving & Debugging Skills

Additional Details :

- Work Mode : Remote

- Contract Type : Contract-to-Hire (C2H)

- Compensation : $200K - $250K (Approx. - 30 LPA)

- Joining : Immediate joiners preferred