Solutions Architect, CustomerLake

Databricks
Amsterdam, London
Workplace: OnsiteFull timeFunction: Solutions Engineering & Sales EngineeringEducation: bachelorsSkills: ["Technical leadership","Consultative advisory","Customer collaboration","Presentation and demo delivery","Roadmap influence"]

Lead strategic customer implementations for Customer Lake, Databricks’ agentic CDP built into the Data Intelligence Platform. Provide technical leadership across customer data, marketing technology, identity resolution, audience activation, and agent workflows—driving adoption from Customer 360 build-out through augmentation or replacement. Deliver demos, POCs, and workshops, translate field insights into roadmap recommendations, and act as tier-3 escalation for complex, mission-critical customer scenarios.

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FursaFursa
Databricks
Databricks
1 day ago

Solutions Architect, CustomerLake

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Last checked: 19 hours agoStatus: Live

Job Summary

Lead strategic customer implementations for Customer Lake, Databricks’ agentic CDP built into the Data Intelligence Platform. Provide technical leadership across customer data, marketing technology, identity resolution, audience activation, and agent workflows—driving adoption from Customer 360 build-out through augmentation or replacement. Deliver demos, POCs, and workshops, translate field insights into roadmap recommendations, and act as tier-3 escalation for complex, mission-critical customer scenarios.
Location: Amsterdam, 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 successful implementations spanning customer data and marketing projects, from architecture to data engineering, identity resolution, and agent deployment.
  • •Collaborate with GTM leadership and account teams to design and execute engagement strategies across the territory, driving adoption from initial Customer 360 build-out through CDP augmentation or replacement.
  • •Act as a trusted advisor and expert Solutions Architect with CMOs, heads of marketing technology, data engineering leaders, and marketing/analytics teams to drive product adoption and vision.
  • •Enable clients at scale through workshops, POC execution, and customer-facing collateral that demonstrates value of an embedded, agentic CDP architecture.
  • •Serve as tier-3 escalation for the most complex technical challenges and refine sales qualification and POC intake to ensure well-scoped engagements.

Key Requirements

  • •5+ years in customer data platforms (CDP), marketing technology (MarTech), or customer data engineering, including 3+ years in a customer-facing pre-sales or consulting role.
  • •Design and implement 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, implementation, identity resolution, audience activation, and migration strategies.
  • •Strong understanding of customer data and governance, including first-party/third-party/enrichment data, identity graphs, consent/privacy signals, and destination systems (ad platforms, email/SMS, CRM, analytics).
  • •Hands-on cloud experience in AWS, Azure, or GCP, plus an undergraduate degree (or higher) in a technical field.
Experience:Customer data platforms (CDP)Marketing technology (MarTech)AdtechData engineeringIdentity resolutionAudience activationAgentic AI
Education:Bachelor's
Skills:Technical leadershipConsultative advisoryCustomer collaborationPresentation and demo deliveryRoadmap influence
Languages:English
Tech Stack:Customer LakeData Intelligence PlatformCDPCustomer 360SQLIdentity resolutionSegmentationPersonalizationNext-best-actionAgentic AI workflowsAudience activationSalesforce Data CloudAdobeSegmentTreasure DataBrazeUnity CatalogGenieReverse-ETLAWS

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