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Tier-1 brand, mid-level generalist Azure data engineer role in metros increases applicant competition.
Role requires Azure data platform skills which are moderately specific but transferable across industries.
Explicit 3-8 years and mandatory Azure Databricks/ADF/ADE skills make filters strict.
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Lead design and development of Azure cloud-based data pipelines and data warehousing solutions leveraging Azure Data Factory, Databricks, and Spark.
Translate client business requirements into technical designs and best practice solutions focused on data ingestion, integration, transformation, and modeling.
Collaborate within Agile/DevOps teams to deliver scalable, performant cloud analytics implementations including reusable components and frameworks.
3 to 8 years of professional experience in data engineering, specifically with Azure cloud services.
Proficient in Azure Data Factory, Azure Databricks, Apache Spark (Python/Scala), and Azure data platform components (SQL Data Warehouse, Data Lake, Cosmos DB).
Bachelor's degree in Engineering or Technology (BE, B.Tech) or MCA or M.Tech; MBA also mentioned but not explicitly required.
Experience with DevOps processes including CI/CD and Infrastructure as Code; hands-on with cloud-based analytics solutions.
Strong expertise in designing and implementing cloud data pipelines and warehouse solutions using Microsoft Azure and Databricks technologies.
Experienced in applying data warehousing modeling principles (e.g., Kimball) and developing security models in data platforms.
Comfortable working in Agile/DevOps environments, collaborating cross-functionally, and evolving technical best practices for scalable analytics delivery.