Description

Design and develop data pipelines within an AWS environment to ingest, process, and analyze large datasets.

This role is on-site.

Responsibilities

• Build data pipelines using AWS Glue, PySpark, or PyShell.
• Implement ETL/ELT processes to manage data movement and transformation.
• Apply dimension modeling techniques using Snowflake and Star schema architectures.
• Optimize database performance through SQL query tuning.
• Manage data ingestion and processing workflows.

Required Skills

• 5+ years of experience in data engineering roles.
• Strong proficiency in Python and SQL.
• Hands-on experience with AWS Glue and PySpark.
• Experience with AWS Lambda, Kinesis, and Step Functions.
• Working knowledge of Aurora MySQL and API Gateway.
• Experience with cloud data warehouses such as Redshift or Snowflake.
• Deep understanding of dimension modeling, including keys and types of dimensions and facts.

Preferred Skills

• Experience working within the Finance or Banking domain.

Key Skills

Education

Any Graduate