Solutions Architect, CustomerLake

Databricks
Munich, London
Workplace: OnsiteFull timeFunction: Solutions Engineering & Sales EngineeringExperience: 5+ yearsEducation: bachelorsSkills: ["Relationship building","Technical leadership","Collaboration","Consultative communication","Problem solving"]

Lead customer-facing architecture and technical discovery for Customer Lake, Databricks’ agentic CDP built natively into the Data Intelligence Platform. Partner with marketing and data stakeholders to run workshops, demos, and POCs spanning identity resolution, audience activation, and agentic AI workflows. Provide tier-3 escalation for complex technical challenges, influence product roadmap with field insights, and help shape qualification and POC intake processes.

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FursaFursa
Databricks
Databricks
2 days ago

Solutions Architect, CustomerLake

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Last checked: 4 hours agoStatus: Live

Job Summary

Lead customer-facing architecture and technical discovery for Customer Lake, Databricks’ agentic CDP built natively into the Data Intelligence Platform. Partner with marketing and data stakeholders to run workshops, demos, and POCs spanning identity resolution, audience activation, and agentic AI workflows. Provide tier-3 escalation for complex technical challenges, influence product roadmap with field insights, and help shape qualification and POC intake processes.
Location: Munich, London
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Provide technical leadership from architectural design through data engineering, identity resolution, audience activation, and agent deployment to drive successful implementations.
  • •Collaborate with GTM leadership and account teams to design and execute engagement strategies that drive Customer Lake adoption across your territory.
  • •Act as a trusted advisor and expert Solutions Architect, delivering presentations, demos, and POCs to drive informed adoption decisions.
  • •Enable clients at scale through workshops, POC execution, and development of customer-facing collateral demonstrating an embedded, agentic CDP architecture.
  • •Handle complex technical challenges as a tier-3 escalation point and translate field insights into recommendations for Product and Engineering teams.

Key Requirements

  • •5+ years of customer data platform (CDP), marketing technology (MarTech), or customer data engineering experience, including designing and delivering client-facing customer data and activation solutions (3+ years in customer-facing pre-sales or consulting).
  • •Design and implement data and AI applications for marketing/customer engagement, including identity resolution, segmentation, personalization, next-best-action, and agentic AI workflows for audience building and campaign activation.
  • •Deep familiarity with CDP and martech/adtech platforms, including composable-CDP architectures and experience with implementation, identity resolution, audience activation, and migration strategies.
  • •Strong understanding of the customer data landscape, including first-party data, third-party/enrichment data, identity graphs, consent/privacy signals, and martech/adtech destinations.
  • •Hands-on experience building solutions in major public clouds (AWS, Azure, or GCP) and a technical undergraduate degree or higher.
Experience:5+ yearsCDPMarketing technology (MarTech)Customer data engineeringAdtechIdentity resolution
Education:Bachelor's in Computer Science, Data Science, Applied Mathematics, Engineering, or similar
Skills:Relationship buildingTechnical leadershipCollaborationConsultative communicationProblem solving
Languages:English
Tech Stack:Customer LakeDatabricksLakehouseAgent BricksLakeflowLakebaseUnity CatalogSQLGenieReverse-ETLIdentity resolutionAudience activationSalesforce Data CloudAdobeSegmentTreasure DataBrazeAWSAzureGCP

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