Azure Data Engineer with Databricks
Posted Updated
Summary
Designs and builds data lake and pipeline solutions in Azure, working hands-on with Databricks, Azure Data Factory, SQL and PySpark. Day to day involves data modeling, ELT/ETL design, lakehouse/Medallion architecture, CI/CD for data workflows and Power BI integration.
- Hands-on experience with implementing solutions with data lakes and pipelines (Databricks, Azure Data Factory).
- Proven experience in designing and implementing solutions in Azure cloud (knowledge of AWS, GCP clouds will be an additional advantage).
- Proficiency in SQL, PySpark, data modeling (3NF, star/snowflake schemas) and ELT/ETL design patterns (knowledge of popular ETL tools, including Azure Data Factory).
- Experience with Python or similar scripting languages for data transformation, orchestration, and automation.
- Familiarity with advanced Databricks features (Unity Catalog, MLflow, Jobs & Pipelines).
- Understanding cloud data architecture principles, including data Lakehouse concepts, Medallion architecture, API integration, and event-driven architecture.
- Experience with CI/CD and DevOps practices for data workflows (Git, Azure DevOps) and analytics integration (e.g., Power BI).
- Excellent communication and client-facing skills, with the ability to explain technical concepts clearly to team members and stakeholders.
- Strong collaboration skills across multidisciplinary teams.