Go-To-Market (GTM) Digital Natives Program Leader

About the Role

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Register Login Try Databricks Overview Culture Benefits Diversity Engineering Research Students & new grads Back to search results Go-To-Market (GTM) Digital Natives Program Leader San Francisco, California; United States Apply now SLSQ127R420 While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. As the GTM Digital Native Programs Leader , you will operate as the de facto COO and scale pipeline and consumption for th high growth Databricks’ Digital Native vertical. You will partner in a "two-in-a-box" model with the Industry GTM Leader to translate strategy into durable, repeatable commercial execution across a rapidly scaling global field organization. You will work closely with sales and field engineering leaders to ideate, build, execute and scale global programs. You will play a critical role in shaping Databricks’ growth trajectory. You will be part of a lean GTM leadership that powers sellers to deliver measurable business outcomes through scale & leverage. You will be the lead orchestrator for your industry vertical, at the center of a mandate to inspire executives, drive industry outcomes, and unleash Databricks’ partner ecosystem in the high-growth SaaS space. The Impact You Will Have Strategy & Operating Model Operating Model Ownership: Own and implement end-to-end op-model (across Sales, FE, Product, Engineering, Developer Relations, Partners) in a consistent global approach. Product-GTM Strategy: Inform the annual Digital Native strategy by synthesizing product telemetry and engineering roadmaps with field signals to identify Big Bets in the digital natives space. Data-Driven Product Feedback: Synthesize learnings from internal (field, product, engineering, developer relations) & external (customer, partner, developers) stakeholders into durable best practices Market Presence & Influence Internal Executive Influence: Wield two-way influence on Databricks’ Field (Sales, FE, Business Dev), Product & Engineering leadership: i.e., reflect industry signals in product roadmaps, as well as translate product activation goals into verticalized industry programs Market Presence: Own and engage with technical & business customer and partner executives, build market presence to uncover signals on technical friction, business value and Databricks differentiators. Industry Evangelism: Serve as a visible evangelist & thought leader (e.g., open source advocacy, scaling AI adoption), representing Databricks’ at key customer, partner, industry and developer forums Execution & Accountability Full-Funnel Program Design: Select & design the industry’s programs across products (and verticalize product programs) across the full funnel: demand generation → pipe creation & progression → consumption Asset Creation: Create high-quality and scalable program assets that will be used by the full field (Sales, FE, BD, Marketing, Ecosystem) at scale Field Activation & Community: Drive continuous field adoption of program assets and outcomes by cross-pollinating best practices across product and field teams in high-impact community cadences. Ecosystem Integration: Collaborate with the partnership, ISV, and Data Marketplace teams to drive adoption of a seamless, interconnected data-sharing ecosystem. Outcome Measurement: Deliver commercial outcomes by establishing measurement and monitoring systems that track product telemetry, industry & partner program performance. Executive Accountability: Drive cross-functional leadership accountability for program adoption and outcomes through continuous monitoring and executive influence. What We Look For Strategic & Operational Mindset COO Mindset: Proven ability to act as the operational backbone of a business vertical, focusing on pipeline health, organizational efficiency, and execution. Strategic Execution: A track record of defining and translating complex industry strategies into durable, "field-ready" commercial motions for large organizations. Programmatic Vision: Experience developing global, scalable GTM frameworks - moving beyond "one-off" deals to create a scalable engine for growth. Technical & Domain Expertise Technical Chops: Technical knowledge on Databricks critical for this market. Comfort with discussing AI & LLM, Lakehouse, Lakebase, governance Industry POV: A strong point of view on macro trends in high-growth SaaS and key persona triggers, helping to shape our industry advantage against peers. Open Source Knowledge: A strong understanding of the open-source ecosystem and how it integrates with proprietary enterprise platforms. AI Builder Experience: Proven track record of hands-on experience building AI systems (MLOps, GenAI apps, or large-scale predictive models). Execution & Analytical Skills Full-Funnel Expertise: Deep understanding of sales play mechanics, including lead generation, pipeline progression, and consumption drivers. Scale Orientation: A "multiplier" mindset with a passion for activating large-scale field organizations and cross-pollinating best practices. Entrepreneurial Spirit: A "doer" mindset with the ability to operate in a fast-paced, ambiguous environment and drive results across cross-functional teams. Leadership & Scale Influence Without Hierarchy: Ability to influence & drive outcomes across senior executives & global teams via influence, clarity & presence versus direct reporting lines. Cross-Functional Orchestration: Skill in collaborating with Product, Engineering, and BD leadership to align product roadmap shifts with commercial requirements specific to high-growth SaaS customers. 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 base 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 anticipated 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 which range your location is in visit our page here . Zone 1 Pay Range $269,800 — $370,900 USD Zone 2 Pay Range $269,800 — $370,900 USD Zone 3 Pay Range $269,800 — $370,900 USD Zone 4 Pay Range $269,800 — $370,900 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, please visit https://www.mybenefitsnow.com/databricks . 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. 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