Senior Product Manager, Data, CDP & Analytics

Das ist der Job

Why this role Data is the operating substrate of an AI-native company.

Darum lohnt es sich

We have the platform, the customers, and a dedicated AI Labs team. You will productize the CDP, build the identity service every other DC product trusts, and replace legacy reporting with a modern analytics surface dealers actually use.

What you'll own The CDP. the company's customer data platform — ingestion, unification, audience modeling, and activation — productized for dealer operators and consumed by every internal product team. Modern analytics. You partner with our AI Labs team and our engineering org to ship identity-aware, data-driven agentic capabilities.

Small team, high talent density, AI augmentation everywhere.

Benefits Paid Time Off Nine (9) Paid Holidays 401(k) plus employer match Health Insurance Flexible Spending Account Health Savings Account Dental Insurance Vision Insurance Short/Long-Term Disability Insurance Employer-paid Life Insurance Additional Voluntary Life Insurance Accident Insurance Critical Care Insurance Hospital Indemnity Insurance Employee Assistance Program Equal Opportunity Statement the company is an Equal Opportunity Employer.

Every customer interaction we run for a dealer — sales, service, F&I, payments — is signal that should compound into smarter engagement, sharper reporting, and increasingly autonomous agents. What we need is the product owner who can see the data layer as one system — CDP, identity and consent, and customer-facing analytics — and ship it.

You will own the data product layer end to end. You will be the single accountable owner of DC's data foundation. This is not a maintenance role. This is the role that turns DC's data into compounding leverage for every product we ship and every agent we deploy. One platform, one roadmap, one owner. Identity and consent.

The identity graph that resolves dealer customers across DMS, CRM, web, and engagement signals — deterministic and probabilistic matching, individual and household, with a clean consent and privacy management model. Every product and every AI agent at DC depends on it. The dealer-facing analytics surface.

Embedded reporting, dashboards, and self-serve exploration that dealers use to run their business — not the legacy reporting story we are retiring. Outcomes that matter. Data activation rate, identity match precision and recall, dashboard MAU and stickiness, and agent personalization lift attributable to identity signal.

You define the metric stack, instrument it, and report against it. The customer relationship for data. You are the product face of the company to the people in dealerships who consume data — GMs, BDC managers, marketing directors, and the operators downstream.

You will run a dealer data council and be the most trusted voice in the company on what dealers actually need from their data. How we work AI-native by default. You own the data layer as a product. Engineering builds the infrastructure. AI Labs builds the agents. You define what we are building and why. Customer-zero culture.

PMs at the company spend time with the people who use our products. For data, that means dealer GMs, BDC managers, marketing operators, and the internal vertical PMs who depend on you. If you only want to build for engineers, this is not the role. Lean and dense. We do not hire to fill org charts.

We hire to multiply the leverage of the people already here. Direct exposure. You report to the VP of Product and have weekly skip-level access to the CPBO. You will work directly with the VP of Engineering and the AI Labs lead. No political layers. What you'll bring 5+ years of product management.

With at least 3 years building productized CDP, identity, embedded analytics, or comparable data platform products at a B2B SaaS company. Pure data engineering or analytics engineering tracks without shipping product to a non-developer buyer will not clear the bar. Demonstrated AI shipping history.

You have shipped LLM-, agent-, or AI-powered features in production. You can walk us through the architecture, the data and identity signal it depended on, the evals, the observability story, the failures, and what you would do differently. We will ask. AI-native PM workflows. Claude, ChatGPT, Cursor, or equivalent are not occasional tools for you.

They are how you do PM work every day. You have strong, defensible opinions about how AI changes discovery, spec writing, prototyping, and customer research, and you can articulate the difference between AI as a feature and AI as an operating model. CDP or comparable data product experience.

You have shipped product at a pure-CDP company (Segment, mParticle, Hightouch, Census, RudderStack, ActionIQ, Tealium, BlueConic, Amperity, or comparable) or at a vertical-SaaS data product (Toast Data, ServiceTitan, Procore, Veeva, BlackLine, or comparable) where you owned a customer-facing data, identity, or analytics surface.

Identity resolution fluency. You have opinions on deterministic vs. probabilistic matching, individual vs. household resolution, identity merge tradeoffs, and how identity signal flows into downstream product surfaces. You don't have to write the matching algorithm — but you have to make the call between two architectures and defend it.

Strategic-with-fluency technical depth. You can read SQL, reason about schemas, pressure-test a data engineer's proposal, and make tradeoff calls on data modeling, pipeline architecture, and reverse ETL without getting out-argued. Strategic with technical fluency, not technical depth that should live with engineering. Cross-functional shipping.

Track record of shipping with engineering, design, data, and GTM partners. You know how to write a spec that engineers respect, ship a launch that PMM can sell, and instrument a product so support can debug it. Operator energy. You move fast, write clearly, push back when you disagree, and take ownership without being asked.

You treat your manager as a peer, not a parent. Bonus points You have shipped data products in a vertical SaaS context to non-developer operators (retail, services, healthcare, hospitality, automotive). You have direct dealership operator experience or close family in the business — but this is a tiebreaker, not a prerequisite.

You have built or operated identity stitching, consent management, or privacy-by-design infrastructure (CCPA, CPRA, GDPR equivalents). You have shipped agent-aware data products — features where an AI agent is a first-class consumer of identity and audience signal.

You have worked with embedded analytics platforms (Sigma, ThoughtSpot Embedded, Looker Embedded, Cube, custom-built). We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other protected characteristics.

All qualified applicants are encouraged to apply. #J-18808-Ljbffr