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Tier-1 brand and metro location but specialized Databricks skill reduces applicant pool.
Cloud Databricks skills are transferable across industries, though financial domain knowledge moderately favored.
Multiple mandatory platform and language skills but no explicit years requirement.
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Own large-scale data engineering implementation on Databricks platform across Azure and AWS clouds.
Manage Databricks platform components including Notebooks, Clusters, Jobs, Delta Lake, Unity Catalog, and RBAC configuration.
Optimize Spark jobs and implement CI/CD pipelines using Azure DevOps for automated deployments.
Proven experience as Data Engineer working extensively with Databricks on Azure cloud; AWS experience is a plus.
Proficient in Scala, Python, PySpark, SQL, and Apache Spark optimization techniques.
Experience with Azure services: Data Factory, Blob Storage, Azure Databricks, and CI/CD using Azure DevOps.
Work Experience Required: Not explicitly mentioned in the JD
Experienced in managing both cloud platforms (Azure primary, AWS secondary) in production data engineering environments.
Strong hands-on skills in Databricks platform operation, including security and governance with Unity Catalog and RBAC.
Technical orientation with ability to debug, optimize code, and implement secure coding principles in data pipelines.