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Reputable brand, common Senior Data Engineer title, and Mumbai metro increase qualified candidate density.
Azure Databricks and PySpark skills are transferable, though financial controls add moderate domain specificity.
Specific Azure Databricks, ADF and PySpark stack plus financial controls create strict technical filters.
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Maintain and enhance data control environments to reduce operational risk and support improved customer outcomes.
Build and operationalize data solutions using Azure services including Azure Data Factory, Azure Databricks, Azure Data Lake Gen 2, and Azure SQL.
Migrate on-premise data warehouses to cloud platforms on Azure and manage data engineering tasks like ingestion, transformation, capacity planning, and performance tuning.
Experience with Azure data services: Azure Data Factory, Azure Databricks, Azure Data Lake Gen 2, Azure SQL.
Proficient in Py-Spark and experienced in relational and dimensional data modeling including big data technologies.
Experience migrating on-premise data warehouses to Azure cloud platforms.
Work Experience Required: Not explicitly mentioned in the JD.
Comfortable working in secured Azure environments using Azure KeyVaults, Service Principals, and Managed Identities.
Experienced in offshore team collaborations and project lifecycle activities including requirements analysis, testing, and releases.
Capable of stakeholder management, process adherence, planning, documentation, and direct business interaction for requirement gathering and query resolution.