Sr. Solutions Architect, Customer Lake

Databricks · United States · Field Engineering - Other · listed September 4, 2026

The shape of it

Seniority
Principal
Experience asked
2+ years
Where
Not stated
Stated pay
$219,100 – $301,300 USD
Requirements listed
0
Length
963 words

In the posting’s own words

Marketing teams are stuck between fragmented customer data and martech stacks that copy that data into proprietary silos while customers expect real-time, personalized experiences. Customer Lake , the agentic Customer Data Platform (CDP) built natively into Databricks, changes that equation. It unifies first- and third-party data into governed Customer 360 profiles, resolves identities, and uses agents to build audiences, recommend next-best actions, and activate campaigns across channels, all without copying data out of the Lakehouse or adding vendor lock-in.

What the job covers

  • Provide technical leadership to guide strategic customers to successful implementations on customer data and marketing projects, ranging from architectural design to data engineering to identity resolution, audience activation, and agent deployment
  • Collaborate with GTM leadership and account teams to design and execute high-impact engagement strategies across your territory, driving Customer Lake adoption from initial Customer 360 build-out through full CDP augmentation or replacement.
  • As a trusted advisor, serve as an expert Solutions Architect building technical credibility with CMOs, heads of marketing technology (MarTech), data engineering leaders, and marketing and analytics teams to drive product adoption and vision.
  • Enable clients at scale through workshops, POC execution, and developing customer-facing collateral that increases technical knowledge and demonstrates the value of an embedded, agentic CDP architecture.
  • Influence product roadmap by translating field-derived, data-driven insights into strategic recommendations for Product and Engineering teams.
  • Handle the most complex technical challenges in this product line by acting as the tier-3 escalation point for the field, ensuring customer success in mission-critical, customer-facing data environments.
  • Establish and refine the sales qualification and POC intake process, ensuring well-scoped engagements that maximize customer success and minimize friction for R&D.
  • Build strong relationships with both internal and external business partners, contributing to broader goals and growth
  • Drive thought leadership through mentoring and knowledge sharing
  • 5+ years in a customer-facing, pre-sales, or consulting role influencing technical executives, driving high-level customer data and marketing strategy, and product adoption.
  • Minimum 2+ years of experience implementing modern data estate, CDP, and Lakehouse architectures with a focus on data and AI applications.
  • Experience with design and implementation of data and AI applications for marketing and customer engagement, including identity resolution, segmentation, personalization and next-best-action, and agentic AI workflows for audience building and campaign activation.

Degree language

  • Undergraduate degree (or higher) in a technical field such as Computer Science, Data Science, Applied Mathematics, Engineering or similar.

Tools and skills named

Go to market
  • Customer success2×
  • Go-to-market2×
  • Solutions architecture2×
Data
  • Data warehouse3×
  • Databricks2×
Cloud & infra
  • AWS
  • Azure
  • GCP
Languages
  • Python
  • SQL
Models & research
  • Machine learning
Product & design
  • Roadmap
Ways of working
  • Mentorship

Words the posting leans on

  • customer23×
  • data23×
  • marketing9×
  • customer data7×
  • customer lake7×
  • experience6×
  • technical6×
  • adoption5×
  • cdp5×
  • product5×
  • agentic4×
  • drive4×
  • engagement4×
  • activation3×
  • audience3×
  • build3×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

The posting, your resume, and the gaps between them. One click loads all three.

More open at Databricks

every open role at Databricks

How this page was made

An automated read of a public job posting, fetched September 4, 2026 and last changed by Databricks on September 4, 2026. Every list above is pulled from the posting’s own sentences — nothing rewritten, nothing added, no judgment about the role or the company. Counts and seniority are read off the text by rule, so they can be wrong where the posting is unusual. The original is the only thing that binds. Openings close without warning; check the source before spending an evening on it.