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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 roleAs 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.
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.
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).
#LI-hybrid
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
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.
Skills Required
- Approximately six or more years of experience in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role, or equivalent demonstrated depth.
- Hands-on coding ability in Python and SQL, including building, debugging, and demonstrating working solutions live.
- Experience with distributed data systems, production cloud deployments using AWS, Azure, or GCP, scalable pipelines, streaming, lakehouse patterns, infrastructure, security, and governance.
- Proficiency with the Databricks Platform or demonstrated ability to ramp quickly on new technologies.
- Experience leading architecture discussions, design reviews, trade-off analysis, recommendations, and business-value translation with senior technical and executive stakeholders.
- Comfort with ambiguity, time-boxed engagements, strong prioritization, variety, and high-impact work.
- Databricks Data Engineer, ML, or Platform certifications.
- Familiarity with Snowflake, AWS native services, Azure Synapse, and competitive positioning.
- Background in a data/AI company or cloud provider.
- Depth in an industry vertical such as financial services, healthcare, retail, or media.
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
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Healthcare Strength — Company materials highlight comprehensive medical, dental, and vision coverage alongside mental-health resources, wellness reimbursements, and business travel insurance. Offerings are described as broad and modern, with core health coverage consistently emphasized.
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Parental & Family Support — Paid parental leave is explicitly called out, with details such as up to 20 weeks for birthing parents and up to 12 weeks for non-birthing parents in the U.S. Public materials also reference family-forming support, reinforcing the focus on families.
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Wellbeing & Lifestyle Benefits — Wellness programs and perks include gym reimbursement, periodic wellness events (e.g., yoga, massages), and in-office meals and snacks in many locations. Personal development funds and discounts further enhance lifestyle and growth support.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
