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Tier-1 employer, mid-level data engineer, metro location, broad Azure/Databricks skillset.
Core data engineering skills are transferable, but Azure/Databricks specialization raises industry bias to medium.
Mandatory 6+ years plus specific Azure, Databricks, Python and SQL requirements enforce strict filtering.
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Design, develop, and manage scalable, secure data pipelines using Azure Databricks and Azure Data Factory on the Azure cloud platform.
Write efficient, reusable Python code for cloud automation, data processing, and orchestration within cloud-native data solutions.
Lead architecture and optimization of ETL workflows, data modeling for OLTP/OLAP, and integration of advanced analytics and BI tools in Azure ecosystem.
6+ years of overall experience in cloud or data engineering roles, with at least 2-3 years hands-on with Azure cloud services and Python development.
Strong Python programming skills, advanced scripting, automation, and cloud SDK experience (Must-Have).
Strong SQL skills and hands-on experience with Azure Databricks, Azure Data Factory, Azure Blob Storage/Data Lake, Apache Spark, and Git (Must-Have).
Bachelor’s degree (BE/B.Tech) or Master of Business Administration (MBA) or MCA.
Experienced in architecting, building, and optimizing data pipelines and data warehousing solutions on Azure cloud using Python and Databricks.
Deep expertise in cloud-native tools for scalable ETL workflows, data modeling, and BI integration, with strong operational ownership of data engineering projects.
Capable of performing code reviews, troubleshooting performance bottlenecks, and staying updated with latest Azure and Python ecosystem advancements.