Partner Manager & Sales Executive, Databricks

Responsibilities

• Own the Databricks Commercial vertical. Build a named-account list of 25–50 target mid-market and enterprise commercial accounts across financial services, healthcare, manufacturing, or retail.
• Originate qualified pipeline. Lead with personal network activation, Databricks field team engagement, Databricks Summit presence, cloud marketplace partnerships (AWS, Azure, GCP), and disciplined account-based outreach. Own a quarterly pipeline contribution target tracked in HubSpot.
• Lead complex pursuits. Run multi-stakeholder, 3–12-month commercial sales cycles from first conversation through security review, legal, and contract close. Engage Resultant’s Databricks engineering and solution architects early.
• Co-sell with Databricks and the cloud ecosystem. Build joint pursuit plans with the Databricks commercial field team, AWS, Azure, and GCP marketplace teams. Operate inside Databricks deal registration discipline. Understand when to bring in the right Databricks AE and how to work alongside cloud partners without burning bridges.
• Partner & Alliance Management
• Own Resultant’s Databricks private-sector relationships. Build and maintain working relationships with Databricks private-sector field teams: AEs, SEs, and practice leads across sports/entertainment and gaming, financial services, healthcare, and manufacturing.
• Develop and execute a co-sell strategy. Conduct territory mapping and account targeting with Databricks private-sector field teams. Ensure Databricks private-sector sellers have current Resultant content, case studies, and contacts at their fingertips.
• Represent Resultant in the market. Attend and speak at Databricks Data + AI Summit, Databricks field events, and vertical industry conferences (Money20/20, HLTH, Gartner Data & Analytics Summit). Contribute thought leadership and become a recognized voice on enterprise AI and data platform modernization.
• Create one-pagers, case studies, and reference stories tailored to private-sector verticals. Coordinate with Resultant’s delivery and SA teams to keep Databricks certifications and partner portal profiles current.
• Advance Resultant’s partnership tier. Coordinate with Databricks enablement programs and work toward tier advancement. Align partner activity to active pipeline in coordination with Resultant’s private-sector BD team.

Qualifications

• 8+ years of progressive enterprise sales and/or alliance management experience, with at least 5 years selling Databricks (or directly competitive data platform) solutions into commercial enterprises across financial services, healthcare, manufacturing, retail, sports/entertainment, or gaming verticals.
• Active Databricks ecosystem relationships - you know the Databricks commercial field organization, the major SI partners, and the cloud marketplace teams at AWS, Azure, and GCP. Private-sector experience required; this is not a public-sector role.
• Track record managing ISV or cloud partner relationships, not just internal sales roles. Experience with Databricks co-sell, deal registration, and partner program mechanics is strongly preferred.
• Consistent quota attainment of $3M+ in annual new bookings across multi-year tenure. References on file.
• Priced fluency in MEDDPICC, Challenger, and Strategic Selling (or other structured sales methodology). These are operating habits, not training certifications.
• Commercial procurement command: you understand enterprise SaaS/services contracting, marketplace transactions (AWS, Azure, GCP Marketplace), MSA/SOW structures, and security review processes. You have closed deals through these vehicles.
• Experience in Sports & Entertainment is a significant differentiator. Familiarity with a comparable platform (Snowflake, GCP, Azure) from a go-to-market perspective is also valued.
• Willingness to travel up to 40% - primarily to client headquarters, Databricks events, cloud partner QBRs, and Resultant offices in Indianapolis and Atlanta.
• Bachelor’s degree required. Advanced degree in computer science, data science, business, or a related technical field preferred.