Description

You will design, develop, and maintain scalable data pipelines and ETL processes on AWS and Databricks.

This role is on-site.

Responsibilities

• Develop and optimize data warehouses and data lakes using PySpark and AWS platforms.
• Implement data ingestion, transformation, and orchestration workflows using AWS Step Functions, Lambda, and Glue Jobs.
• Monitor, troubleshoot, and optimize pipeline performance using AWS CloudWatch and other monitoring tools.
• Collaborate with data analysts, data scientists, and business stakeholders to define data requirements.
• Ensure data quality, governance, and security across all data systems and workflows.

Required Skills

• 5+ years of professional experience in data engineering.
• Strong proficiency in Python.
• Hands-on experience with Databricks.
• Experience implementing workflows using AWS Glue.
• Expertise in ETL Processes development.
• Familiarity with AWS services (Step Functions, Lambda).
• Knowledge of CI/CD practices.

Key Skills

Education

Any Graduate