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Tier-1 brand, mid-level data engineer title, broad Databricks/Azure skillset, and likely metro location increase competition.
Databricks- and cloud-centric skillset limits cross-industry portability.
Multiple mandatory platform skills (Databricks, Unity Catalog, Azure, PySpark) enforce strict technical filtering.
Own and implement data engineering solutions at large scale using Databricks platform including Notebooks, Clusters, Jobs, and Delta Lake.
Configure and manage Unity Catalog and Role-Based Access Control (RBAC) for data governance.
Develop, debug, and optimize data processing workflows using Scala, Python, PySpark, SQL on Azure cloud services with CI/CD pipelines through Azure DevOps.
Proven experience in Data Engineering with extensive hands-on on Databricks platform and Azure cloud services.
Expertise in Databricks components: Notebooks, Clusters, Jobs, Delta Lake; Unity Catalog and RBAC configuration.
Proficient programming skills in Scala, Python, PySpark, and SQL including debugging and optimization abilities.
Work Experience Required: Not explicitly mentioned in the JD.
Experience working on both Azure and AWS cloud platforms with Databricks as a core technology.
Strong operational knowledge of data governance, compliance, and secure coding principles in Databricks environment.
Comfortable delivering large scale data engineering projects, including CI/CD implementation using Azure DevOps, with ability to articulate technical concepts effectively.