Req ID: FEQ327R409

The team

The Fungible team is the “rapid-response squad” within the Field Engineering organisation that engages with customers on the most strategic, highest-potential opportunities across Benelux and the Nordics to accelerate critical use cases, land technical wins, and drive successful Databricks adoption. If you enjoy working on novel use cases across a variety of industries on highly visible engagements, this is the right home for you!

The role

As a Fungible Solutions Architect, you lead the technical strategy on time-boxed, targeted engagements - typically one to five months - aimed at accelerating a specific set of critical customer workloads from evaluation to a production-grade technical win. You own the architecture conversation, drive platform adoption, and act as a trusted advisor to customer architects and engineering leaders, then transition the momentum you've built to the core account team.

You bring technical depth and the judgment to apply it fast, in situations that require strong ownership and are highly visible. Where a specialisation helps you contribute quickly, great — but on this team, breadth, adaptability, and a bias for impact matter just as much as your area of depth.

The impact you will have

• Accelerate what matters most: parachute into strategic, high-profile opportunities and own a clearly defined technical area, moving critical workloads and use cases from evaluation toward production and consumption.
• Lead the architecture: design scalable, production-grade solutions across data engineering, ML/AI, and real-time analytics, and lead the whiteboarding, design reviews, and trade-off decisions with senior customer stakeholders.
• Win the technical decision: demonstrate Databricks' differentiation through custom-built solutions in competitive, must-win scenarios.
• Move fast while maintaining the bar: establish momentum quickly in ambiguous situations and compress timelines without cutting corners.
• Hand off, don't hold on: package your progress into a clean transition to core SAs, DSAs, specialists, or partners so wins are sustained and expanded after you move to the next engagement.
• Scale: bring back patterns, plays, and product feedback that make every engagement after yours faster.

What we look for

We care more about how you think and the impact you've had than about a specific checklist. You'll likely bring most of the following, and if you're missing one or two but bring something we haven't thought of, we still want to hear from you!

• Several years of experience (typically ~6+) in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role, or a track record that demonstrates equivalent depth.
• Hands-on coding ability in Python and SQL, with the ability to build, debug, and demonstrate working solutions live.
• Depth in distributed data systems and production cloud deployments (AWS, Azure, or GCP), scalable pipelines, streaming, and lakehouse patterns, plus the infrastructure, security, and governance to run them.
• Proficiency on the Databricks Platform, or a demonstrated ability to ramp on new technology quickly. A strong "spike" in an area such as real-time/streaming, ML/AI, data governance, or migrations helps you add value fast.
• Experience leading architecture discussions with senior technical stakeholders, design reviews, trade-off analysis, clear recommendations, and translating complex architecture into business value for both engineers and executives.
• The temperament this team runs on: comfort with ambiguity and time-boxed engagements, strong prioritisation, and a genuine preference for variety and high-impact work.

Nice to haves

Given our role in the Field Engineering organisation, we are always looking to expand the depth our team can offer with your areas of specialisation. Any of the following would be a valuable addition to the team!

• Databricks certifications (Data Engineer, ML, or Platform).
• Familiarity with competitive platforms (Snowflake, AWS native services, Azure Synapse) and how to position against them.
• Background in a data/AI company or cloud provider.
• Depth in an industry vertical (Financial Services, Healthcare, Retail, Media, and others).

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