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Strong brand, metro location, and popular Data Engineer title create moderate competition.
Azure Databricks expertise is transferable, but enterprise governance and finance context give moderate industry specificity.
Explicit 8+ years requirement plus mandatory Azure/Databricks skills and leadership make filters strict.
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Architect and deliver scalable enterprise-scale Azure data lakehouse platforms using Databricks, Delta Lake, and related Azure services.
Lead and mentor a team of data engineers, drive Agile delivery including sprint planning, estimation, and technical roadmaps.
Implement CI/CD, security governance, monitoring, and operational readiness for production data platforms.
8+ years of experience in data engineering or cloud data platform development including 4+ years on Microsoft Azure.
Strong hands-on expertise with Azure Databricks, Apache Spark, PySpark, Delta Lake, Azure Data Factory, and Synapse.
Bachelor's degree in Computer Science, Engineering, Information Technology, Data Engineering or equivalent practical experience.
Not explicitly mentioned in the JD: Notice period requirements.
Experienced senior engineer capable of hands-on delivery and setting engineering standards in Azure data platforms with Databricks.
Proven leader who has guided teams, reviewed architecture and driven delivery in Agile/DevOps environments.
Strong expertise in modern data platform patterns including lakehouse architecture, data governance, and performance/cost optimization on Azure.