Description

You will build and optimize AWS-based data pipelines for ingestion, transformation, and data delivery.

This role is on-site.

Responsibilities

• Develop ETL jobs using PySpark and AWS Glue, managing schema handling and transformations.
• Implement data quality checks and monitoring to ensure pipeline reliability.
• Design partitioning, file formats, and storage strategies in AWS to improve query performance.
• Collaborate with analytics and engineering teams to integrate data products.
• Optimize large-scale data processing for scalability and performance.

Required Skills

• 6-12 years of Data Engineering experience.
• Strong proficiency in AWS data services, specifically S3, Glue, and EMR.
• Hands-on experience with PySpark for distributed data transformations.
• Proven track record in ETL development and pipeline deployment.
• Experience with data quality validation and testing.
• Ability to tune performance for large-scale data pipelines.

Preferred Skills

• Experience with advanced AWS Glue features for complex transformations.

Education: B.E., B.Tech, or M. Tech in Computer Science or related field.

Key Skills

Education

Any Graduate