Manager, Field Engineering - Strategic Accounts Germany
DatabricksBerlin, Germany; Munich, GermanyPosted 7 April 2026
Job Description
FEQ427R177
Germany’s strategic Manufacturing and Energy customers are at an inflection point: AI is moving from pilots to platform decisions. This is a rare, once-per-cycle transition where the platform choice will set the pace for the next decade of industrial AI in Germany – shifting from data programmes to AI-driven operations at scale.
This role combines people leadership, business ownership, and executive engagement. You will operate as a player-coach in critical deals while building a high-performing, scalable field-engineering organisation for a consumption-based business.
You report to the Director, Field Engineering.
The impact you will have:
Build, lead, and scale the pre-sales (Solutions Architect) team for Strategic Manufacturing and Energy customers in Germany, including hiring, coaching, performance management, and career development, and owning coverage for complex industrial stakeholder environments.
Own pre-sales ROI and effectiveness, including coverage models, prioritisation, and impact on win-rate, sales cycles, and customer adoption
Act as a player-coach in strategic opportunities by balancing hands-on involvement in the most critical customer engagements with building repeatable motions, artefacts, and coaching mechanisms that scale impact across the team.
Establish and reinforce a solution- and value-based selling culture, focused on business outcomes, not just technical excellence
Partner closely with Sales leadership to support forecast accuracy, pipeline quality, and consumption growth in a usage-driven business model
Engage with C-level and senior executives at strategic customers to build trusted relationships and long-term partnerships
Drive a scalable adoption model by anchoring partner and PS attach nd establishing a crisp pre-/post-sales handshake tied to consumption outcomes (onboarding readiness, adoption milestones, expansion path).
Represent Field Engineering as part of the regional leadership team, contributing to Databricks’ brand, market positioning, and growth in Germany
What we look for:
Proven experience building and managing pre-sales or technical field teams in a high-growth environment
Strong background in data engineering, analytics platforms, databases, or data science, gained through engineering, consulting, or technical leadership roles
Demonstrated success in consumption-based or SaaS business models, including forecasting, expansion, and customer adoption
Ability to operate as a player-coach, balancing hands-on deal involvement with scalable team leadership
Track record of partnering effectively with Sales and cross-functional leaders to drive measurable business outcomes
Experience establishing repeatable processes that improve efficiency without limiting innovation or ownership
Passion for the data and AI market and the ability to articulate a clear, executive-level POV on the value of Databricks
Executive presence with the ability to influence and communicate confidently at C-level
Fluent German (highly preferred) and fluent English (required)
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
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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 ca ... (truncated, view full listing at source)
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