Description

Build and maintain scalable data pipelines on AWS using PySpark, Databricks, and AWS Glue.

This role is on-site.

Responsibilities

• Develop and maintain ETL/ELT pipelines using PySpark and Databricks.
• Build data ingestion and transformation workflows using AWS Glue and related AWS services.
• Write and optimize SQL queries for data modeling, validation, and performance tuning.
• Implement scalable data processing patterns in Spark for large datasets.
• Collaborate on data quality checks, monitoring, and troubleshooting of production data jobs.

Required Skills

• 6+ years of experience in data engineering.
• Strong experience with AWS for building and managing data pipelines.
• Hands-on experience with Python, PySpark, and Databricks.
• Strong SQL skills for data transformation and performance optimization.
• Experience with ETL/ELT processes.

Preferred Skills

• Experience with Hadoop.
• Data modeling expertise.

Education: Any Graduate.

Key Skills

Education

Any Graduate