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Manager, Field Engineering (Pre-Sales) – Benelux Named Accounts

Databricks · Amsterdam, Netherlands

Confidence
Medium confidence
Posted
5 Oct 2026
First seen
24 Oct 2026
Last checked

Evidence

Medium confidence

Databricks is on the Dutch IND register. The posting doesn’t mention visas.

Sponsor register

Dutch IND public register of recognised sponsors

Listed as Databricks. KVK 51208121. Snapshot 26 Oct 2026.

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Job posting

Doesn’t mention visas or relocation.

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Still open

Seen on the job board

First seen 24 Oct 2026. We check every day and remove closed roles.

Where you apply

databricks.com

Databricks’s job board.

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About the role

(FEQ427R544) Role Summary As a Field Engineering Manager, you will lead a high-performing team of technical pre-sales Solutions Architects (SAs) dedicated to enterprise Named Accounts across the Benelux region. You will operate at the intersection of deep technology and business strategy, driving platform adoption and enterprise AI initiatives.

As a technically credible coach and AI builder , you will spend meaningful time in the field (~30-40%) partnering with customer executives and internal Sales counterparts. You will lead by example to instil an AI-Builder Mindset across your team, establish rigorous operational inspection cadences, coach SAs through complex architecture designs without taking the pen, and decisively build an elite pre-sales organisation.

The Impact You Will Have • Build & Scale Elite Teams: Hire, mentor, and retain exceptional Solutions Engineers/Architects in the Benelux region, establishing high standards for technical excellence, inclusive leadership, and decisive performance management. • Drive AI Adoption & Capabilities: Lead by example as an AI practitioner, embedding AI tools into team workflows and driving scalable capability across the organisation. • Act as a Customer Advisor: Build trusted relationships with C-level and senior technical executives across customer accounts. Translate complex platform capabilities into measurable business ROI (e.g., predictive maintenance, yield optimisation, supply chain resilience).

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