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Niche Databricks/Azure requirements reduce candidates, but Tier-1 brand and hybrid remote increase applicant volume.
Strong platform-specific (Azure Databricks, Delta Lake) and architecture expectations limit cross-industry transferability.
Mandatory 7+ years and deep Azure Databricks and platform expertise make shortlisting highly selective.
Architect and build end-to-end cloud-native data platforms using Azure and Databricks technologies with focus on Delta Lake architectures and scalable ETL/ELT pipelines.
Lead data governance, security, and compliance implementation including GDPR, RBAC/ABAC, and data quality frameworks across the data platform.
Collaborate with stakeholders to define data strategy, conduct architectural reviews, and mentor teams on Azure, Databricks, and scalable data design principles.
7+ years of experience in Data Architecture or Data Engineering roles.
Expert-level skills in Azure Databricks (Spark, Delta Lake, MLflow), Azure Data Lake Gen2, Azure Data Factory/Synapse Pipelines, and Azure SQL/Cosmos DB.
Strong proficiency in PySpark, SQL, and Python programming languages.
Bachelor's degree or higher in Computer Science, MIS/IT, Mathematics, Engineering or equivalent work experience.
Experienced in designing and optimizing large-scale distributed data systems with hands-on expertise in cloud-native Azure ecosystem and Databricks.
Proven ability to lead architectural strategy and governance frameworks in enterprise environments, balancing technical and business requirements.
Familiar with data governance tools (e.g., Azure Purview), data mesh concepts, domain-driven design, and continuous integration/deployment processes.