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Databricks › Engineering

Solutions Architect - CPG and Manufacturing

Databricks · Zurich

Pay
Not listed
This company didn't publish a range
Posted
Sep 3, 2026
Tracked open for 52 days
Team
Field Engineering - Other
Full-time
Databricks hiring
896 open roles
583 in engineering
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Typical solutions engineer pay at startups: $214K median, middle half $181K–$235K (494 posted ranges).

Typical engineering pay at Databricks: $182K–$250K — median of 306 listed ranges.

Across all startups we track: $170K–$242K for engineering roles (8,046 listed ranges).

About the role

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As a Solutions Architect, you will contribute to the technical strategy for your customers — owning architecture discussions, driving platform adoption, and serving as a trusted technical partner to customer architects and engineering leads. You combine deep technical expertise with a hands-on builder mindset to position Databricks as the foundation of your customers' data and AI strategy. You are developing a technical specialization (archetype) and are becoming a go-to resource within your team for depth in a specific domain.

The Impact You Will Have:

  • Own the end-to-end technical strategy for your accounts — from discovery through production deployment — driving competitive wins by building differentiated AI and data solutions that accelerate consumption growth
  • Lead complex architecture discussions — designing production-grade solutions across data engineering, AI/ML, agentic systems, and real-time analytics
  • Serve as a trusted technical partner to customer architects, engineering leads, and Directors — helping shape their data and AI journey on Databricks
  • Develop an emerging technical specialization (archetype) — ideally in AI/ML, agentic architectures, or a related domain — becoming a go-to resource within your team
  • Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver end-to-end AI and data solutions for complex customer needs
  • Provide structured feedback to product teams on customer requirements, AI capabilities, and competitive gaps

What We Look For:

  • 6+ years in solutions architecture, data engineering, data science/AI, or technical pre-sales — with a strong track record of hands-on solution building and customer-facing technical leadership
  • Deep expertise in modern data and AI architectures — lakehouse design, scalable pipelines, real-time/streaming, and cloud-native platforms — with the ability to lead architecture discussions with senior stakeholders through whiteboarding, design reviews, and trade-off analysis that connect data foundations to AI/ML outcomes
  • Strong understanding of AI/ML concepts, agentic architectures, and ontology design — including experience with compound AI systems, autonomous agent frameworks, knowledge graphs, and semantic data models that enable intelligent, context-aware applications
  • Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area (e.g., AI/ML, agentic systems, real-time/streaming, data governance, migrations)
  • Experience with production deployments on public cloud (AWS, Azure, or GCP), including security and governance considerations
  • Track record of driving platform adoption and consumption growth — particularly across AI/ML and data analytics workloads
  • Excellent communication skills — able to translate complex AI and data architectures into business value for technical and executive audiences
  • Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)

Nice to Have:

  • Databricks certifications (Data Engineer, ML Associate/Professional, Platform)
  • Experience with competitive platforms (Snowflake, AWS native services, Azure Synapse) — understanding the landscape you'll position against
  • Background in an AI-first company, data platform vendor, or cloud provider
  • Industry domain expertise, preferably in CPG and Manufacturing (Financial Services, Healthcare, Retail, Media, etc. also valued)

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.

From Databricks's careers page. First seen Sep 5, 2026, last verified Oct 27, 2026.

Databricks hiring momentum

Open roles: 896, up 1 (+0%) over the last 30 days.

Jul 15, 2026 · 782Oct 27, 2026 · 896

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