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Tier-1 brand, popular data-engineer role, metro location, and broad required tech stack increase applicant density.
Data engineering skills transfer across industries but Azure/Databricks specificity moderates portability to medium.
Explicit 6+ years requirement plus mandatory Python, Databricks, SQL, Spark and Azure skills makes filtering strict.
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Design, develop, and manage scalable, secure data pipelines using Azure Databricks and Azure Data Factory.
Write and optimize cloud automation and data processing code primarily in Python, implementing cloud-based data solutions integrating structured and unstructured data.
Lead code reviews, troubleshoot ETL performance, and contribute to enterprise-level data warehousing solutions within the Azure ecosystem.
6+ years of overall experience in cloud or data engineering roles, including 2-3 years hands-on with Azure cloud services and strong Python development.
Proficiency in Python programming, advanced SQL, and practical experience with Azure Databricks and Azure Data Factory.
Education requirement: BE/B.Tech, MBA, or MCA degree.
Experience with data modeling (normalization/denormalization), Azure Data Lake/Blob Storage, Apache Spark, and Git version control.
Experienced in building and optimizing scalable ETL workflows and cloud-native data solutions on Azure platform.
Strong developer familiar with Python scripting for automation and cloud SDK use, with a focus on clean, reusable code and version control best practices.
Capable of troubleshooting performance issues and integrating BI and advanced analytics use cases in enterprise data environments.