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Strong employer brand, popular Databricks data engineer role, metro location, and broad skill requirements.
Databricks and cloud skills transfer, but financial governance increases domain sensitivity.
Multiple mandatory Databricks, cloud, and language skills required, increasing technical screening rigidity.
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Own end-to-end data engineering implementation at large scale using Databricks platform on Azure and AWS clouds.
Manage Databricks platform components including Notebooks, Clusters, Jobs, Delta Lake, Unity Catalog, and RBAC configuration.
Optimize Apache Spark, PySpark, and SQL code and implement CI/CD pipelines using Azure DevOps for data workflows.
Expertise in Databricks platform (Notebooks, Clusters, Jobs, Delta Lake), Unity Catalog, and RBAC configuration.
Strong experience with Azure Cloud services including Data Factory, Blob Storage, Azure Databricks, and CI/CD using Azure DevOps.
Proficient in Scala, Python, PySpark, and SQL programming for data processing.
Work Experience Required: Not explicitly mentioned in the JD.
Experience managing large scale data engineering projects on cloud platforms (Azure and AWS) with a focus on Databricks.
Technical expertise in secure coding, data governance, and compliance related to data processing.
Able to debug, optimize complex Spark and PySpark code and implement continuous integration/delivery solutions in a hybrid cloud environment.