Looking for Data Engineers

Minimum 6+ years in Data Engineering, with at least 4 years of hands-on experience in Databricks and Azure ecosystem — this is a must.

• End-to-End Data Pipeline Delivery – Proven track record of building and owning ETL/ELT pipelines, data models, and platform components at enterprise scale across complex business domains.

• Expert SQL Skills – Advanced proficiency in complex joins, window functions, CTEs, query optimization, and performance tuning across large datasets.

• Strong PySpark & Python – Hands-on experience building distributed data processing pipelines, transformations, and automation scripts using PySpark and Python.

• Databricks Expertise – Deep working knowledge of Delta Lake, Unity Catalog, Workflows, medallion architecture (bronze-silver-gold), notebook development, and lakehouse best practices.

• Clean Code & Engineering Discipline – Writes modular, well-documented, and testable code. Follows coding standards, maintains version control hygiene, and builds reusable components that other developers can extend.

• Problem Solving & Debugging – Strong ability to diagnose and resolve complex data pipeline failures, distributed system issues, and production incidents under pressure.

• Performance Tuning – Demonstrated expertise in optimizing Spark jobs, SQL queries, and storage layers for cost efficiency, throughput, and reliability.