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Strong employer brand, metro location, and a broadly popular mid-level data engineer profile raise competition.
Core data engineering skills are transferable, but Azure/Databricks focus increases industry specificity.
Explicit 6+ years requirement and mandatory skills like Databricks, Azure, Python, SQL make filtering strict.
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Design, develop, and optimize scalable, secure data pipelines on Azure using Databricks, Data Factory, and Python.
Architect and implement cloud-based data solutions integrating structured and unstructured data, managing Azure Data Lake and Blob Storage.
Lead code reviews, troubleshoot data flow performance issues, and contribute to enterprise data warehousing and BI integration.
6+ years total experience in cloud or data engineering; at least 2-3 years hands-on with Azure cloud services.
Strong Python programming skills with 2-3 years hands-on development experience.
Proficient with Azure Databricks, Azure Data Factory, SQL, Apache Spark, and data modeling (normalization and denormalization).
Education: BE/B.Tech/MBA/MCA; Master of Business Administration preferred.
Experienced in building scalable ETL pipelines and cloud-native data architectures within Azure ecosystem.
Capable of leading code quality initiatives and managing version control using Git.
Familiar with integrating advanced analytics and BI tools, with some awareness of OLTP/OLAP systems and Agile delivery methodologies.