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Tier-1 employer, metro location, and popular mid-level data engineer skillset drive high competition.
Core data engineering skills transfer broadly, but Azure/Databricks focus reduces cross-industry fit somewhat.
Explicit 6+ years plus mandatory Azure, Databricks, Python and Spark requirements make screening strict.
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Design, develop, and manage scalable, secure data pipelines using Azure Databricks and Azure Data Factory.
Develop and optimize ETL workflows integrating structured and unstructured data sources across the Azure cloud platform.
Write clean, efficient Python code for cloud automation, data processing, and orchestration; lead code reviews and ensure version control compliance.
6+ years of overall experience in cloud or data engineering roles, with 2-3 years hands-on Azure cloud services experience.
Strong proficiency in Python programming, advanced SQL, and Azure Databricks mandatory.
Experience with Azure Data Factory, Azure Blob/ Data Lake Storage, Apache Spark, and data modeling required.
Education: BE/B.Tech/MBA/MCA degree mandatory.
Experienced in architecting and implementing cloud-based data solutions focusing on Azure ecosystem.
Skilled in building and optimizing enterprise-class ETL pipelines and data warehousing solutions.
Hands-on developer with expertise in Python scripting, Azure services, and working knowledge of Git version control.