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Mid-level data engineer in a metro, popular skills and broad requirements increase competition.
Core data engineering skills are broadly transferable across industries, lowering background sensitivity.
Explicit 5+ years plus mandatory Databricks/DBT/Azure skills make shortlisting strict.
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Design, develop, and maintain Business Translation Layer (BTL) data pipelines using SQL and DBT in Azure Databricks.
Create and manage build and release pipelines using GitHub, Azure DevOps, and Harness for Databricks deployments.
Monitor, diagnose, and improve performance of BTL jobs ensuring data pipeline integrity and quality across environments.
Minimum 5 years of experience with strong proficiency in data warehousing concepts.
Hands-on experience with SQL, database design, and data transformation logic development.
Experience working with Azure Databricks and Azure cloud platform components (Azure Synapse, ADLS).
Experience with GitHub, build management tools, and release pipelines (Azure DevOps / Harness).
Experienced in software development focused on data ingestion, transformation, and storage of large datasets with distributed computing knowledge.
Skilled at optimizing and troubleshooting complex data pipelines within enterprise-scale data environments.
Able to collaborate cross-functionally to integrate data pipelines into broader system architecture and maintain secure, high-quality codebases.