Azure Data Engineer Databricks

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Experience Required - 6 Years

Must Have Technical/Functional Skills

Design, build, and orchestrate ETL/ELT pipelines using Azure Databricks.

• Implement batch data ingestion and transformations using PySpark and Spark SQL.
• Architect and maintain Lakehouse and analytical warehouse models (fact and dimension schemas) leveraging Delta Lake.
• Ensure data quality, reliability, lineage, and governance across the data platform.
• Collaborate with security and platform teams to enforce data access controls and best practices.
• Experience on CI/CD pipelines using Git for Databricks
  
  

Roles & Responsibilities

• Act as the onsite lead for Azure Databricks data engineering initiatives.
• Supervise and guide an offshore development team, assigning work, reviewing deliverables, and ensuring adherence to best practices.
• Perform code reviews, design reviews, and solution walkthroughs for offshore-developed components.
• Ensure alignment between offshore execution and onsite architecture, security, and business requirements.
• Proactively identify risks, gaps, and improvement opportunities across the data platform.
• Prior experience working in a hybrid onsite offshore delivery model
  
  

Generic Managerial Skills, If any

• 6-10 years of hands on experience in data engineering.
• Strong, proven expertise in Azure Databricks and Delta Lake.
• Advanced proficiency in SQL with a solid understanding of distributed data processing concepts.
• Demonstrated experience leading, mentoring, or supervising data engineering teams.
• Strong experience performing code reviews and solution design validations.
• knowledge of data security, and access management (RBAC).
• Preferred / Nice to Have Skills: Experience with Azure Synapse / Fabric, Azure Data Factory.