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Tier-1 brand, mid-level Databricks/Azure data engineer in metro creates high applicant competition.
Core Databricks and Spark skills are broadly transferable across industries with minimal domain dependency.
Multiple mandatory Databricks, cloud, language, and governance requirements create strict technical shortlisting.
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Own end-to-end data engineering and implementation at scale using Databricks on Azure and AWS clouds.
Manage Databricks platform components including Notebooks, Clusters, Jobs, Delta Lake, Unity Catalog and RBAC configuration.
Optimize Apache Spark, debug and enhance PySpark/SQL code, and implement CI/CD pipelines with Azure DevOps.
Expertise in Databricks platform including Notebooks, Clusters, Jobs, Delta Lake, Unity Catalog, and RBAC.
Strong programming skills in Scala, Python, PySpark, and SQL.
Experience in Azure cloud services including Data Factory, Blob Storage, Azure Databricks.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced data engineer with large scale implementation expertise on both Azure and AWS clouds.
Proficient in Apache Spark optimization and secure coding with strong focus on data governance and compliance.
Skilled in CI/CD practices using Azure DevOps, with ability to communicate complex technical concepts effectively.