Description

You will build, maintain, and optimize scalable data pipelines and warehousing solutions on AWS.

This role is on-site.

Responsibilities

• Design and implement ETL/ELT workflows using AWS Glue, Lambda, EMR, and Step Functions.
• Build and optimize data lakes using S3, Glue Catalog, and Lake Formation.
• Develop and manage data warehousing solutions using Amazon Redshift.
• Troubleshoot day-to-day pipeline issues and ensure timely resolution.

Required Skills

• 5+ years of professional experience in data engineering.
• Strong proficiency in PySpark for large-scale data processing.
• Hands-on experience with AWS services: S3, Glue, EMR, Lambda, and Redshift.
• Proficiency in SQL for querying and data transformation.
• Experience building and managing data pipelines on AWS.
• Familiarity with data ingestion tools like Kinesis or Kafka.
• Understanding of data lake architecture and best practices.

Key Skills

Education

Any Graduate