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Protocol Intelligence
Data-driven signals on your job's competitivenessMetro location, known brand, and niche Databricks/managerial requirements yield medium applicant competition.
Core data engineering management is transferable, but Databricks and governed-AI emphasis raises medium sensitivity.
Explicit 10+ years, 3+ years management, Databricks and FinOps requirements create high shortlisting strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Lead and grow the engineering organization managing the Databricks-based data and AI ecosystem, including the Data Platform and AI/Data Engineering teams.
Own a unified technical strategy and delivery accountability integrating GenAI, data engineering, platform governance, and FinOps with 99.99% platform reliability commitments.
Manage people leadership, FinOps budgeting, executive stakeholder engagement, and governance/risk oversight across combined engineering programs.
Minimum Requirements
10+ years in data/software engineering with 3+ years managing engineering leads, managers, or senior ICs in distributed teams.
Strong working knowledge of the Databricks ecosystem (Unity Catalog, Delta Lake, Databricks Workflows, etc.) sufficient to evaluate architecture and coach leads.
Experience with cloud platform/FinOps budget ownership and driving cost-efficiency across teams.
Work Experience Required: 10+ years data/software engineering including management experience as above.
Ideal Candidate Profile
Experienced engineering leader able to integrate GenAI and data platform governance into unified delivery and strategy roadmaps.
Capable of synthesizing technical trade-offs from multiple teams into coherent executive communications and decisions.
Track record of building high-performing engineering teams with proven people development, career pathing, and retention focus.