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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.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
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
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Databricks San Francisco, California, USA Office
160 Spear Street, San Francisco, CA, United States, 94105
Databricks Mountain View, California, USA Office
351 E Evelyn Ave Mountain View, CA USA, Mountain View, United States, 94041
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