Solutions Architect, CustomerLake

Databricks
London
Workplace: OnsiteFull timeFunction: Solutions Engineering & Sales EngineeringExperience: 5+ yearsEducation: bachelorsSkills: ["Technical leadership","Relationship building","Consultative advisory","Problem-solving","Strategic thinking"]

Lead technical engagements for Customer Lake, an agentic CDP built into the Databricks Data Intelligence Platform. Provide architecture guidance from identity resolution and governed customer data to audience activation, next-best actions, and agentic AI workflows. Partner with GTM and account teams on engagement strategies, deliver demos and POCs, handle complex tier-3 escalations, and translate field insights into recommendations for product and engineering.

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FursaFursa
Databricks
Databricks
1 day ago

Solutions Architect, CustomerLake

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Job Summary

Lead technical engagements for Customer Lake, an agentic CDP built into the Databricks Data Intelligence Platform. Provide architecture guidance from identity resolution and governed customer data to audience activation, next-best actions, and agentic AI workflows. Partner with GTM and account teams on engagement strategies, deliver demos and POCs, handle complex tier-3 escalations, and translate field insights into recommendations for product and engineering.
Location: London
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Provide technical leadership to guide strategic customers through Customer Lake implementations across architecture design, data engineering, identity resolution, audience activation, and agent deployment.
  • •Collaborate with GTM leadership and account teams to design and execute engagement strategies that drive adoption from initial Customer 360 build-out through augmentation or replacement.
  • •Act as a trusted advisor and tier-3 escalation point, building technical credibility with marketing and data engineering leaders and handling complex mission-critical technical challenges.
  • •Enable clients at scale via workshops, POC execution, and customer-facing collateral that explains the embedded, agentic CDP architecture.
  • •Influence product roadmap and field processes by translating field-derived insights into recommendations and establishing/refining sales qualification and POC intake for well-scoped engagements.

Key Requirements

  • •5+ years in customer data platform (CDP), marketing technology (MarTech), or customer data engineering, including client-facing customer data and activation solution delivery (3+ years in customer-facing pre-sales/consulting).
  • •Experience designing and implementing data/AI applications for marketing and customer engagement, including identity resolution, segmentation, personalization, next-best action, and agentic AI workflows.
  • •Deep familiarity with CDP and martech/adtech platforms, including composable-CDP architectures and implementation, identity resolution, audience activation, and migration strategies.
  • •Strong understanding of the customer data landscape, including first/third-party data, identity graphs, consent/privacy signals, and martech/adtech destinations.
  • •Experience operationalizing customer data as governed data products (audience/segment definition in SQL or natural language, reverse-ETL/activation pipelines, and metric/identity/consent governance in Unity Catalog).
Experience:5+ yearsCustomer data platformCDPMarketing technologyMarTechAdtechData engineeringCloud
Education:Bachelor's in technical field such as Computer Science, Data Science, Applied Mathematics, Engineering or similar
Skills:Technical leadershipRelationship buildingConsultative advisoryProblem-solvingStrategic thinking
Languages:English
Tech Stack:Customer LakeDatabricks Data Intelligence PlatformCDPCustomer 360Identity resolutionAudience activationAgentic AISQLGenieUnity CatalogReverse-ETLSalesforce Data CloudAdobeSegmentTreasure DataBrazeAWSAzureGCPMartech/adtech

Company Brief

Databricks
Provides a unified data analytics platform powered by Apache Spark to simplify building, deploying, and scaling data engineering, data science, and machine learning workloads for enterprises.
Industry: Data Infrastructure
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series E+
Headquarters: San Francisco, United States
Founded: 2013
WebsiteLinkedIn