Senior Solutions Architect - Lakewatch

Databricks Databricks · Data AI · London, United Kingdom · Field Engineering - Other

This role focuses on applying AI and cybersecurity expertise to design and implement customer-facing security solutions, specifically within the Lakewatch product line. The Solutions Architect will guide strategic customers, drive product adoption, and influence the product roadmap by translating field insights into recommendations for Product and Engineering teams. Key responsibilities include technical leadership, engagement strategy, enabling clients through workshops and POCs, and acting as a tier-3 escalation point for complex technical challenges.

What you'd actually do

  1. Provide technical leadership to guide strategic customers to successful implementations on big data projects, ranging from architectural design to data engineering to model deployment
  2. Collaborate with GTM leadership and account teams to design and execute high-impact engagement strategies across your territory, driving Lakewatch adoption from initial data offload through full SIEM augmentation or replacement.
  3. As a trusted advisor, serve as an expert Solutions Architect building technical credibility with CISOs, security architects, SOC leadership, and security analysts to drive product adoption and vision.
  4. Enable clients at scale through workshops, POC execution, and developing customer-facing collateral that increases technical knowledge and demonstrates the value of an open agentic SIEM architecture.
  5. Influence product roadmap by translating field-derived, data-driven insights into strategic recommendations for Product and Engineering teams.

Skills

Required

  • 5+ years of cybersecurity engineering, security operations (SecOps), or security architecture expertise
  • 3+ years in a customer-facing, pre-sales or consulting role
  • design and implementation of data and AI applications in cybersecurity
  • anomaly detection
  • behavioral analytics
  • agentic AI workflows for triage and investigation
  • SIEM platforms (Splunk, Microsoft Sentinel, QRadar, or similar)
  • deployment, tuning, detection engineering, and migration strategies
  • security telemetry landscape (endpoint, network, identity, cloud, SaaS logs)
  • detection-as-code workflows
  • rule authoring in SQL or YAML
  • CI/CD integration for detection pipelines
  • MITRE ATT&CK framework mapping
  • SQL
  • Python
  • AI tools
  • public cloud environments (AWS, Azure, or GCP)
  • cloud-native security logging and monitoring
  • security operations
  • data engineering
  • data warehousing
  • AI/ML for security
  • data governance
  • streaming

Nice to have

  • SOAR platforms
  • OCSF standards
  • Global System Integrators (GSIs)
  • third-party consulting organizations

What the JD emphasized

  • 5+ years of cybersecurity engineering, security operations (SecOps), or security architecture expertise
  • proven track record of designing and delivering customer-facing security solutions
  • agentic AI workflows
  • SIEM platforms
  • detection engineering
  • detection-as-code
  • big data projects
  • data engineering
  • model deployment
  • agentic SIEM architecture

Other signals

  • AI applications in cybersecurity
  • agentic AI workflows
  • SIEM augmentation or replacement
  • customer-facing security solutions