Description

You will design, build, and maintain scalable ETL/ELT data pipelines for structured and unstructured data sources.

This role is hybrid.

Responsibilities

• Develop and optimize data solutions using AWS and/or Azure services for ingestion, processing, and storage.
• Build and manage data lakes and data warehouses, implementing data modeling and transformation workflows.
• Optimize data processing performance and ensure data quality through monitoring and troubleshooting.
• Implement data security, governance, and best practices while supporting CI/CD workflows for data engineering assets.

Required Skills

• 6+ years of experience in data engineering and analytics platforms.
• Hands-on experience with AWS (Glue, S3, Redshift, EMR, Lambda, Athena) and/or Azure (Azure Data Factory, Azure Databricks, Synapse Analytics, ADLS).
• Strong SQL and Python skills with experience in Spark or PySpark for data transformations.
• Deep knowledge of ETL/ELT, data warehousing, data modeling, and distributed computing.
• Familiarity with Git and CI/CD processes.
• Degree in Computer Science, Engineering, or related field (or equivalent practical experience).

Key Skills

Education

Any Graduate