Data Engineer

About the Role

We are seeking a Data Engineer with hands-on Databricks experience to build and maintain scalable data pipelines on Azure, delivering reliable lakehouse solutions using medallion architecture.

Key Responsibilities

• Develop batch and incremental pipelines using Databricks (PySpark, Spark SQL) and Delta Lake.
• Orchestrate workflows with Databricks Workflows and Azure Data Factory, following medallion architecture (Bronze → Silver → Gold).
• Deliver analytics-ready datasets for Power BI/Qlik Sense.
• Follow Git-based development, code reviews, and CI/CD practices; monitor and resolve pipeline and data quality issues.

Required Skills

• Solid working knowledge of PySpark, Spark SQL, Delta Lake, and Databricks Workflows/Jobs, with exposure to Spark performance optimization.
• Hands-on experience with Azure Data Factory and ADLS Gen2; familiarity with Azure SQL or other relational databases.
• Understanding of lakehouse/medallion architecture, dimensional modeling (facts, dimensions, SCDs), and data governance fundamentals.
• Strong SQL and Python skills; experience with REST API integrations, Git (Azure DevOps/GitHub), and CI/CD.

Preferred

• Databricks Certified Data Engineer Associate, DP-203, or DP-600.
• Exposure to Microsoft Fabric (Lakehouse, Data Factory, OneLake).

Education & Experience

• Bachelor's degree in Computer Science, IT, or a related field (or equivalent experience).
• 5 years of Data Engineering experience, and  2+ years hands-on with Databricks, in Azure-based environments.