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Protocol Intelligence
Data-driven signals on your job's competitivenessMetro Mumbai and generic senior engineer title increase applicant pool despite niche Databricks specialization.
Databricks-specific platform ownership and data governance reduce cross-industry portability, requiring domain expertise.
Explicit 8+ years, mandatory Databricks platform experience and strict tech stack make screening stringent.
Job Description
Structured overview of role & requirementsAbout This Role
Own and architect the end-to-end Databricks Lakehouse platform including workspace design, compute strategies, and multi-cloud deployment.
Define and enforce global data governance, security, and operational standards via Unity Catalog while ensuring platform reliability and 99.99% availability.
Lead AI-native platform integration and AI-assisted engineering practices; partner with cross-functional teams and drive cost governance and monitoring.
Minimum Requirements
8–10+ years in data engineering or platform roles with at least 3 years directly architecting and operating production Databricks environments.
Proven hands-on experience managing Databricks Lakehouse components: Unity Catalog, Delta Lake, Delta Live Tables, Databricks SQL, cluster/compute policy design.
Strong proficiency in Python, SQL, Apache Spark (batch and streaming), and Infrastructure-as-Code tools like Terraform or Databricks Asset Bundles.
Work Experience Required: 8–10+ years (Senior or Lead Data Engineering/Data Platform role). Education/Certification: Not explicitly mentioned as mandatory; Databricks certifications preferred but optional.
Ideal Candidate Profile
Deep expertise in Databricks platform engineering at scale including governance, cost optimization, and security compliance in multi-tenant enterprise environments.
Strategic thinker capable of translating business requirements into secure, scalable, and automated data platform capabilities with measurable platform availability targets.
Experienced in AI-native data platform features and AI-assisted engineering workflows, able to communicate complex technical concepts effectively to both technical and non-technical stakeholders.