Strategy & Execution Manager

SLSQ227R807

The GTM Strategy & Operations team works directly with Databricks' Sales Leadership to accelerate growth across the business. We empower senior leaders with data-driven insights, scalable systems, and operating mechanisms to shape the high-level strategy and execute in an extremely high-growth environment. We are looking for a Strategy & Execution Manager to serve as the business partner for the EE/Startup leadership team under the AMER Enterprise & Emerging Business BU. This is a critical and visible role to shape the GTM strategy of Databricks' highest-velocity, highest-volume segments, where the operating model has to look meaningfully different from larger-enterprise motions. In this role, you will conduct in-depth analyses, build scalable systems for stakeholders, own operational cadences for the EE/Startup team, and redesign how strategy and ops work gets done in the age of AI. You must be able to deliver the day-to-day operational work with exceptional rigor, while also never losing sight of the long-term strategy and how the business operating model needs to evolve. Alongside the EE/Startup leadership, you'll partner across the broader AEEB and StratOps team on cross-segment initiatives, ensuring we maintain collaboration across the BU and share best practices. The ideal candidate is a self-starter with endless curiosity who can work cross-functionally to tackle complex problems end-to-end. We're looking for someone who is technical, AI-fluent, operationally rigorous, strategic about how high-volume GTM businesses should operate, and biased toward redesigning workflows from first principles rather than maintaining legacy ones. This is a unique opportunity to reshape how Databricks thinks about high-volume GTM businesses, and to set the blueprint for the industry. The work will define what scaled, AI-native GTM operations look like at one of the fastest-growing companies in tech. The impact you'll have Serve as the Strategy partner for the VP, EE/Startup and his leadership team Champion and challenger of the EE/Startup leadership team Redesign operational workflows from first principles in the age of AI — identify which work AI and automation can absorb, where business judgment is irreducible, and design the right operating model for a high-volume segment Redefine what a high-volume GTM business should look like — territory design, New Logo motion, hunter/core ratios, ramp models, partner motions, AI-augmented prospecting. Challenge the operating norms built for a different scale. Independently own analysis with large datasets to guide investment, growth, and capacity decisions Own reporting, forecasting, territory planning, and quota/productivity modeling for the segment Run recurring cadences (QBR deep dives, forecast calls, exec summaries) without hand-holding. You are trusted to run meetings on behalf of your leader. Work cross-functionally with Planning, Recruiting, Commissions, Marketing, and Partner Ops to identify optimization opportunities and resolve business and data challenges Be a force multiplier: bring fresh thinking to old problems, build AI-powered toolkits that scale, and raise the technical bar for the whole team. What we look for AI fluency is non-negotiable. You use AI tools (Codex, Claude, Cursor, Glean, Genie, Databricks Apps, custom agents) as part of your daily workflow as a multiplier. You think in terms of "how should this work be designed given AI?", not "how do we apply AI to existing work?" Strong preference for individuals with a "built something where there wasn't anything" background. Ideal profiles include GTM Strategy at a hyper-growth company, chief of staff at a growth-stage startup, and former consultants who have operational experience. We are looking for individuals who thrive in environments where the playbook didn't exist yet, and you built it. Exceptional attention to detail & data integrity instinct. This role requires consistent, high-quality operational delivery: accurate exec-facing work, on-time delivery, status integrity, zero-defect output. You are able to spot discrepancies and trace them to root causes; you won’t ship a number you can’t defend. Strategy and operations are equally weighted; you have to do both. Operational ownership orientation. You want to do the operational parts of the job, not just architect them. You're a doer as much as a designer. The volume is real, and the work won't get done by deck-building. Business support orientation: You frame technical work around sales leader decisions. You are comfortable operating at a strategic altitude, not just metric-watching. Strategic mind for high-volume GTM. You bring a perspective on how segments serving thousands of accounts should operate — scaled coverage, AL pilots, partner-led motions, programmatic exec engagement. You want to redefine the operating model, not maintain it. Comfort with ambiguity. This role doesn't come with a complete playbook. The right candidate is energized by that. Strong technical depth. Excel/Google Sheets (advanced). Comfort with newer data tools (Databricks SQL, Genie, Lakeview, custom agents) and willingness to learn fast. Less about which tools you've mastered, more about how quickly you pick up new ones. "Get it done" attitude with the ability to architect strategy AND operationalize it with high attention to detail. Excels in a collaborative environment with a high degree of honesty, integrity, and sound judgment. You document and teach what you build. Excellent spoken and written communication. Comfortable presenting to VPs and BU leadership regularly. Produce leader-ready decks, exec summary docs, and quantitative business cases. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding the pay range for your location, visit our page here. Zone 1 Pay Range

$162,900 — $223,950 USD

About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone. #J-18808-Ljbffr Cacheflow