Requisition ID: FEQ427R217
**Sr. Solutions Architect (Lakewatch - EMEA) **
The Solutions Architect (Lakewatch) team executes on Databricks’ strategic Product Operating Model that provides enhanced focus on earlier stage, highly prioritized product lines in order to establish product market fit, and set the course for rapid revenue growth. They are part of a global go-to-market team mandate, though individually will cover a specific, local region. Clients may span across one or more business units and verticals. By working in partnership with direct account teams, they will jointly engage clients, foster the necessary relationships, position in-depth the specific product line, so as to provide compelling reasons for clients to adopt and grow the usage of the given product. They understand the appropriate approach, the guardrails, and the steps needed to successfully adopt the product line, as clients deliver on their business objectives.
The Solutions Architect (Lakewatch) is paired with an Account Executive aligned to the product line with specific targets accordingly. Together, they will devise and implement a strategy across their assigned set of accounts, develop presentations, demos and other assets and deliver them such that customers make an informed decision as they decide to adopt the product-line in a meaningful way.
The Lakewatch product-line requires the following core technical competencies:
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5+ years of cybersecurity engineering, security operations (SecOps), or security architecture expertise, with a proven track record of designing and delivering customer-facing security solutions (of which 3+ years are in a customer-facing, pre-sales or consulting role).
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Experience with design and implementation of data and AI applications in cybersecurity, including anomaly detection, behavioral analytics, and agentic AI workflows for triage and investigation.
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Deep familiarity with SIEM platforms (Splunk, Microsoft Sentinel, QRadar, or similar), including deployment, tuning, detection engineering, and migration strategies. Familiarity with SOAR platforms is also desirable.
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Strong understanding of the security telemetry landscape: endpoint (EDR/XDR), network (firewall, DNS, proxy), identity (Okta, Entra ID), cloud (AWS CloudTrail, Azure Activity Log, GCP Audit), and SaaS application logs. Familiarity with standards such as OCSF.
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Experience with “detection-as-code” workflows, including rule authoring in SQL or YAML, CI/CD integration for detection pipelines, and MITRE ATT&CK framework mapping.
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Credibility in influencing security analytics products with the market insight needed to shape and prioritize roadmap capabilities.
The impact you will have
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Provide technical leadership to guide strategic customers to successful implementations on big data projects, ranging from architectural design to data engineering to model deployment
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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.
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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.
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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.
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Influence product roadmap by translating field-derived, data-driven insights into strategic recommendations for Product and Engineering teams.
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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 security environments.
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Establish and refine the sales qualification and POC intake process, ensuring well-scoped engagements that maximize customer success and minimize friction for R&D.
Competencies & Responsibilities
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5+ years in a customer-facing, pre-sales or consulting role influencing technical executives, driving high-level security strategy and product adoption.
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Experience with design and implementation of data and AI applications in cybersecurity, including anomaly detection, behavioral analytics, and agentic AI workflows for triage and investigation.
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Proficient in programming, debugging, and problem-solving using SQL and Python and with AI tools.
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Experience collaborating with Global System Integrators (GSIs) and third-party consulting organizations to drive customer outcomes in cybersecurity.
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Hands-on experience building solutions within major public cloud environments (AWS, Azure, or GCP), with an understanding of cloud-native security logging and monitoring.
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Deep experience in security operations, with broad familiarity across one or more of the following: data engineering, data warehousing, AI/ML for security, data governance, and streaming.
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Undergraduate degree (or higher) in a technical field such as Computer Science, Cybersecurity, Applied Mathematics, Engineering or similar.
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter , LinkedIn and Facebook .
**Benefits
**At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here .
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
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