Senior Solutions Architect (Pre-sales) - Life Sciences

Databricks - Amsterdam, Netherlands - original posting ->
Status
Open
Remote policy
Not stated
Employment type
Not stated
Salary
Not stated
Categories
Field Engineering - Other
Tech
awssnowflakesparkpythonsoftwaresenior
Source
databricks
First observed
2026-10-05 18:35 UTC
Last seen
2026-10-05 18:35 UTC
Source claims posted
2026-10-05 14:53 UTC
Consecutive misses
0 of 3

What the posting says

(FEQ427R727)

The Role

We are looking for a creative, execution-oriented Senior Solutions Architect to join the Benelux team to maximise the phenomenal market opportunity that exists for Databricks in the Life Science industry. You will bring experience as an architect on large, complex, multinational accounts, and your mission will be to drive the technical and consumption strategy for one of the world's most notable life science companies. This will be driven in partnership with regional account executives and the global account team.

As a Senior Solutions Architect at Databricks, you will come with an informed and compelling point of view on the Data, Analytics and AI space, which will guide your technical strategy and, together with our teams and partners, allow you to provide exceptional value and build lasting trust with executives and technical champions at the account.

The Impact You Will Have

Drive the technical and consumption strategy for the organisation's most complex customer engagements, directly influencing platform adoption and revenue growth.

Own senior-level technical relationships — serving as a trusted advisor on enterprise data and AI strategy.

Lead the most complex architecture engagements: multi-workload platforms, enterprise-wide migrations, real-time systems, and AI/ML at scale, including GenAI and agentic AI workflows (Agent Bricks, AI Functions, LLMOps).

Operate as an Expert on the Databricks Platform with a declared archetype — actively mentoring others and driving horizontal impact across your team.

Develop and execute competitive strategies for your customers, positioning Databricks against incumbent and emerging platforms.

Orchestrate cross-functional teams (Delivery & Specialist SAs, Partners, Product) to deliver enterprise-grade solutions.

Coach and develop junior engineers/architects on technical depth, customer engagement, and use case prioritisation.

Contribute to Field Engineering thought leadership through customer-facing content, workshops, and community engagement.

What We Look For

8+ years of experience in a global/cross-region, multi-architect account team, combining solutions architecture, principal engineering, technical pre-sales leadership in a customer-facing capacity.

Strong hands-on technical background and coding proficiency — Python, SQL, and ideally Spark/PySpark. You will complete a live coding assessment and a platform/prototype build during the interview process.

Deep expertise in enterprise data architecture: distributed systems at scale, streaming/real-time, lakehouse design patterns, data governance frameworks, and cloud-native platforms.

Expert-level data platform knowledge (either in Databricks or a similar modern data & AI platform with demonstrated rapid learning ability).

Recognised as an expert in technical specialisation — e.g., real-time architectures, ML/AI platforms, data governance, large-scale migrations, or industry-specific solutions.

Executive presence — ability to influence Directors, VPs, and C-level stakeholders on long-term data and AI strategy; proven value-based selling and vision-generation skills; ability to lead competitive displacements and complex enterprise evaluations.

Strong strategic thinking — connecting technical architecture decisions to business outcomes and revenue impact. Proven track record of driving consumption growth and platform adoption in large accounts.

Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience); advanced degrees are valued.

Nice to Have:

Databricks certifications.

Prior experience at Databricks, Snowflake, AWS, Google, Microsoft, or a top-tier data/AI company, ideally within Healthcare & Life Sciences (HCLS)/Pharma vertical.

Published thought leadership (blogs, conference talks, open source contributions).

Life Sciences industry vertical expertise with executive-level domain credibility, ideally GxP experience in a pharma setting.

#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.

Quality

Completeness: 45%

Not enough history yet to judge honesty signals.

Timeline

  1. *
    #1188456 2026-10-05 18:35 UTC
    Published