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Senior, niche Databricks specialization reduces applicant density despite Bengaluru market.
Highly Databricks-specific architecture and certification requirements limit cross-industry transferability.
Mandatory 12+ years and required Databricks certifications enforce strict filtering.
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Architect and lead design of enterprise Databricks Lakehouse platforms on Azure, AWS, or GCP, including workspace federation, network isolation, and identity federation.
Drive migration of legacy data warehouses to Databricks, own cluster architecture decisions, and optimize cost and performance.
Lead implementation of data governance via Unity Catalog, AI/ML platform architecture, and stakeholder engagement including CoE standards and mentoring data architects.
Minimum 12 years experience in data architecture, engineering, or enterprise analytics; at least 5 years on Databricks platform delivery.
Databricks Certified Data Engineer Professional or Databricks Certified Associate Developer for Apache Spark required.
Expert proficiency in Apache Spark, Delta Lake, Delta Live Tables, Unity Catalog, and Databricks on major cloud platforms (Azure, AWS, or GCP).
Proficiency with infrastructure-as-code (Terraform, Databricks Asset Bundles), MLflow, SQL for Databricks SQL/Photon, and real-time streaming architectures (Kafka + Autoloader).
Experienced in multi-cloud enterprise Databricks architecture and complex data platform migrations.
Proficient in implementing advanced Databricks governance, security, and AI/ML operational frameworks at scale.
Capable of leading technical stakeholder engagements, developing CoE standards, mentoring teams, and driving Databricks best practices across an organization.