Manager, Delivery Solutions Architects - Financial Services

Databricks Databricks · Data AI · CA · Remote · Delivery Solutions Architects

Manager for Delivery Solutions Architects in Financial Services, focusing on post-sales customer success and driving the adoption of Data and AI solutions. The role involves leading a team, setting technical strategy, partnering with sales and services, and ensuring measurable customer outcomes by moving use cases from kickoff to production.

What you'd actually do

  1. Hire, coach, and develop a high-performing DSA team. Own career growth, calibrated performance management, and individual development plans.
  2. Own capacity planning and investment forecasting across the FINS portfolio. Defend investment decisions with data, alongside sales and field leadership.
  3. Partner with Sales, Pre-Sales, Professional Services, and Systems Integrator partners to accelerate use case delivery and reduce customer risk.
  4. Drive measurable customer outcomes: use-case throughput, time-to-production, consumption growth, and renewal rates. Forecast each across your portfolio.
  5. Bring a programmatic approach to running the business. Build the systems, operating cadences, and playbooks that scale the DSA practice.

Skills

Required

  • 5+ years of experience managing a customer-facing technical team (DSA, Solution Architect, Technical Account Manager, Customer Success Engineer, or equivalent)
  • Demonstrated leadership of a team of pre-sales or post-sales technical talent
  • Track record of putting data and AI workloads into production at scale, e.g., as a delivery architect, project manager, DevOps engineer, or service or product owner
  • Conversant with the business problems and Data and AI use cases in financial services (banking, capital markets, insurance, or asset management preferred)
  • A bias for building systems, not just running them
  • A bias for growing people, not just managing them
  • Track record of overachievement against quota, Goals or similar objective targets
  • Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience through work experience

Nice to have

  • Can travel up to 30% when needed

What the JD emphasized

  • post-sales success
  • Data and AI transforms how they do business
  • move use cases from kickoff to production
  • senior technical talent
  • Hiring, coaching, and growing this team is the heart of the job
  • customer-facing technical team
  • pre-sales or post-sales technical talent
  • putting data and AI workloads into production at scale