Databricks Data Engineering Manager

Lead Data Engineer II role focused on delivering data and AI programs using the Databricks Platform, managing teams, building client relationships, and driving strategic direction in data engineering, BI, and AI/ML. Responsibilities include program leadership, client relationship management, team development, strategic solution design, and technical oversight with a focus on Databricks features like Unity Catalog, MLOps, Agent Bricks, Model Serving, and Genie.

What you'd actually do

  1. Program Leadership: Lead large-scale data and AI programs, serving as the subject matter expert for teams implementing solutions across the entire Databricks platform.
  2. Client Relationship Management: Build and maintain strong relationships with clients, acting as a trusted advisor on their holistic data and AI strategy, providing insights from practical, large-scale project experience.
  3. Team and Practice Development: Lead, coach, and develop teams of data engineers, data scientists, and architects. Support business development and contribute to the growth of the practice.
  4. Strategic Solution Design: Design complex, data-driven solutions and architectures that integrate data engineering, BI, and AI/ML capabilities to meet our clients' strategic technology goals.
  5. Technical Oversight: Provide expert guidance on project delivery, define success criteria, and ensure the adoption of industry best practices for data governance (Unity Catalog), security, and MLOps.

Skills

Required

  • Master's or PhD degree in a relevant STEM field
  • Ability to obtain and maintain a US government security clearance
  • 7+ years of real-world experience leading the delivery of complex, large-scale data and AI initiatives utilizing the breadth of the Databricks platform.
  • 5+ years of experience with the latest Databricks features including Lakeflow Connect, Lakebase, Agent Bricks, Model Serving, Genie, and Databricks Apps.
  • 2+ years of experience leading and managing cross-functional teams of technical professionals on challenging client engagements.
  • 2+ years of experience in data strategy, modern data architectures, data governance, and best practices for enterprise AI built on Databricks.
  • Ability to travel up to 25%, on average, based on the work you do and the clients and industries/sectors you serve

Nice to have

  • Professional Databricks certifications (e.g., Data Engineer Professional, Machine Learning Professional) are highly preferred
  • Exceptional communication and stakeholder management abilities, including experience with executive-level communication.
  • Public sector experience preferred
  • Active public sector clearance preferred

What the JD emphasized

  • 7+ years of real-world experience leading the delivery of complex, large-scale data and AI initiatives utilizing the breadth of the Databricks platform.
  • 5+ years of experience with the latest Databricks features including Lakeflow Connect, Lakebase, Agent Bricks, Model Serving, Genie, and Databricks Apps.
  • 2+ years of experience in data strategy, modern data architectures, data governance, and best practices for enterprise AI built on Databricks.

Other signals

  • Databricks Platform
  • data engineering
  • AI/ML
  • MLOps
  • data governance
  • Model Serving
  • Genie