FEQ327R42

Marketing teams are stuck between fragmented customer data and martech stacks that copy that data into proprietary silos while customers expect real-time, personalized experiences. Customer Lake, the agentic Customer Data Platform (CDP) built natively into Databricks, changes that equation. It unifies first- and third-party data into governed Customer 360 profiles, resolves identities, and uses agents to build audiences, recommend next-best actions, and activate campaigns across channels, all without copying data out of the Lakehouse or adding vendor lock-in.

The Solutions Architect (Customer Lake) team is part of a dedicated, global go-to-market organization focused on driving adoption and revenue growth for Customer Lake, Databricks’ agentic Customer Data Platform (CDP) built natively into the Data Intelligence Platform. The Customer Lake SA will engage clients across business units and verticals, build relationships with marketing and data stakeholders, position Customer Lake in depth, and deliver presentations, demos, and POCs that drive informed adoption decisions. They will understand the guardrails and the steps needed to successfully land and expand Customer Lake as clients deliver on their customer engagement and growth objectives.

The impact you will have

• Provide technical leadership to guide strategic customers to successful implementations on customer data and marketing projects, ranging from architectural design to data engineering to identity resolution, audience activation, and agent deployment
• Collaborate with GTM leadership and account teams to design and execute high-impact engagement strategies across your territory, driving Customer Lake adoption from initial Customer 360 build-out through full CDP augmentation or replacement.
• As a trusted advisor, serve as an expert Solutions Architect building technical credibility with CMOs, heads of marketing technology (MarTech), data engineering leaders, and marketing and analytics teams to drive product adoption and vision.
• Enable clients at scale through workshops, POC execution, and developing customer-facing collateral that increases technical knowledge and demonstrates the value of an embedded, agentic CDP architecture.
• Influence product roadmap by translating field-derived, data-driven insights into strategic recommendations for Product and Engineering teams.
• 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, customer-facing data environments.
• Establish and refine the sales qualification and POC intake process, ensuring well-scoped engagements that maximize customer success and minimize friction for R&D.
• Build strong relationships with both internal and external business partners, contributing to broader goals and growth
• Drive thought leadership through mentoring and knowledge sharing

Competencies & Responsibilities

• 5+ years in a customer-facing, pre-sales, or consulting role influencing technical executives, driving high-level customer data and marketing strategy, and product adoption.
• Minimum 2+ years of experience implementing modern data estate, CDP, and Lakehouse architectures with a focus on data and AI applications.
• Experience with design and implementation of data and AI applications for marketing and customer engagement, including identity resolution, segmentation, personalization and next-best-action, and agentic AI workflows for audience building and campaign activation.
• Facilitate and influence Executive stakeholders while aligning technology strategy to business value and ROI
• Proficient in AI assisted programming, debugging, and problem-solving using SQL and Python.
• Experience collaborating with Global System Integrators (GSIs) and third-party consulting organizations to drive customer outcomes in marketing and customer data initiatives.
• Hands-on experience building solutions within major public cloud environments (AWS, Azure, or GCP), with an understanding of cloud-native data ingestion, activation, and governance.
• Deep experience in customer data and marketing analytics, with broad familiarity across one or more of the following: data engineering, data warehousing, AI/ML for personalization, data governance, and streaming.
• Undergraduate degree (or higher) in a technical field such as Computer Science, Data Science, Applied Mathematics, Engineering or similar.