Data Engineer (Databricks)

Required Skills & Qualifications

• 3-5 years of hands-on experience in Data Engineering with strong Databricks implementation experience (environment setup, cluster configuration, and workflow management).
• Strong experience in building scalable ETL/ELT pipelines using Databricks and PySpark in production environments.
• Solid understanding and practical implementation of Medallion Architecture (Bronze, Silver, Gold layers)
• Experience in designing reusable data frameworks and establishing standardized data processing architecture.
• Strong SQL expertise with experience in complex transformations and performance optimization.
• Hands-on experience with Delta Lake, including partitioning strategies, incremental loads, and data quality checks.
• Strong understanding of data modeling concepts (star schema, fact/dimension modeling, normalization/denormalization)
• Experience with version control systems and CI/CD practices for data pipelines.
• Strong client-facing communication skills with the ability to gather requirements, manage stakeholders, and drive end-to-end ownership.
• Databricks certification (Data Engineer Associate/Professional) is a strong plus. Retail domain familiarity is an added advantage.

Required Academic Qualifications:

• BS/MS Computer Sciences