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Metro Bangalore and visible data role increase competition, but niche Databricks principal requirement limits applicant pool.
Highly specialized Databricks, lakehouse, and Spark expertise limits cross-industry transferability.
Explicit 12+ years plus mandatory Databricks, Unity Catalog, Delta Lake, Spark, and IaC requirements make filters stringent.
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Own and architect the Databricks data platform including Unity Catalog, Delta Lake, cluster configuration, and workflow orchestration.
Lead design and evolution of medallion lakehouse architecture to support BI, GenAI, and ML use cases at scale.
Set architectural standards and technical vision for data pipelines and ML/AI platforms; mentor engineers and troubleshoot production issues.
Minimum 12 years experience in data engineering with 3+ years of hands-on Databricks production experience.
Expertise in Unity Catalog, Delta Lake, Spark performance tuning, and medallion/lakehouse architecture design.
Strong proficiency in SQL, Python, one major cloud platform (AWS, Azure, or GCP), and infrastructure-as-code tooling.
Experience with CI/CD for data pipelines including Databricks Asset Bundles and leading technical decisions/mentoring.
Experienced contributor at architect/principal level with ownership of multi-year data platform roadmaps and technical standards.
Proven ability to lead cross-functional teams in adoption of standards and AI-assisted tooling for data engineering.
Experience designing and scaling data platforms specifically for AI and ML workloads, with migration expertise from legacy systems.