Product Manager, Reporting & Analytics

DriveCentric, Inc. is hiring a Product Manager to fully own the Reporting product line, spanning the new reporting experience, migration from legacy reporting, and a roadmap that supports both customer-facing needs and internal analytics vision. The role reports to the Staff Product Manager for Data, CDP and Analytics and presents product plans to the executive team.

Role Scope

You will own the Reporting product end-to-end, including the new reporting experience and its phased rollout. You will also lead the legacy migration strategy for dealers moving off ad hoc and bespoke reports, while defining how dashboards, a report builder, and self-serve analytics operate across the dealer lifecycle. You will partner closely with data platform and engineering teams to establish standards for data trust and freshness and to shape the AI-native future of reporting with Databricks as the underlying platform.

Responsibilities

• New reporting experience (end-to-end): plan and execute a phased rollout from early access to general availability, including cohort selection, defining a quality gate for phase readiness, establishing launch sequencing, and maintaining the customer-facing reporting roadmap used by CSM teams in the field.
• Phased delivery decisions: determine what ships in each phase and defend the sequencing and tradeoffs.
• Legacy migration: develop a migration approach to move dealers off roughly ten thousand ad hoc and bespoke reports in the old system, using programmatic conversion, dealer self-service migration tooling, and a plan for bespoke enterprise reports that should not be built again.
• Dashboards, report building, and self-serve: own the dealer-facing analytics surface, including dashboards, drill-down, scheduled delivery, date range and attribution controls, and a report builder that enables operators to answer their own question without filing a ticket.
• Packaging strategy: define what belongs in the base product versus a premium SKU.
• Data trust and freshness: partner with the data platform and engineering teams on the dimensional model, ETL cadence, freshness SLAs, and report permissioning; set the bar for “correct and current” and maintain it (without building the pipelines).
• AI-native reporting vision: define what DriveCentric reporting looks like with Databricks underneath, including natural language exploration, agent-generated insight, and anomaly detection; sequence the path toward that vision.
• Visualization craft: own DriveCentric’s visual language for reporting, including chart selection, period-over-period and store-to-store comparison patterns, when a sparkline beats a bar, and how funnel or cohort views map to dealership sales processes; ensure drill-down carries context forward.
• Design collaboration: work with design on a chart library and defaults, and ship visualization behaviors including color, density, and empty or loading states.
• Customer relationship for reporting: serve as the product face of reporting for GMs, BDC managers, controllers, and dealer group executives, as well as internal CSM and support teams who field dealer questions.
• Dealer feedback loop: run a customer advisory group and act as the most trusted internal voice on what dealers need from their data, with expectation of being in dealerships.

Requirements

• Product management experience: 3 or more years in product management, or a comparable path into product from analytics, data, implementation, or dealership operations, with ownership of outcomes and shipping change.
• Automotive retail experience: experience working at a dealership, dealer group, or vendor serving them, with the ability to discuss closing ratio, gross, aged inventory, or BDC appointment set rate, and understanding why CRM data can differ from what a sales manager trusts.
• Fluency with data products: hands-on experience with or near reporting, dashboards, BI, or analytics products; ability to read SQL, reason about a schema, distinguish data problems from UI problems, and pressure-test engineering proposals.
• Migration and legacy instincts: experience moving customers off what they already use comfortably, recognizing migration as a product problem rather than only a project plan, with opinions on how to make the new system worth switching to.
• AI shipping curiosity or history: experience shipping AI-powered features, including the ability to explain how you evaluate output quality and where you would show results to dealers versus keep them internal.
• Clear writing: ability to write specs engineers respect, create launch notes PMM can sell, and provide executive updates that can be read quickly (a writing sample will be requested).
• Operator energy: ability to move fast, push back on disagreements, take ownership without prompting, and treat your manager as a peer.

Technologies

• Claude, ChatGPT, Cursor
• Databricks
• SQL
• Natural language exploration
• Agent-generated insight
• Anomaly detection
• ETL

Bonus Points

• Hands-on with Databricks, Snowflake, Looker, Power BI, Sigma, ThoughtSpot, or comparable embedded analytics platforms.
• Experience running an early access or beta program, including cohort selection scar tissue.
• Ownership of a product line where support escalations were the primary feedback loop.
• Experience with dimensional modeling, ETL tradeoffs, or data quality programs.

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

How We Work

• AI-native by default: Claude, ChatGPT, Cursor, or equivalent are used as part of PM work every day, including research synthesis, spec writing, and prototyping.
• Customer-centric culture: PMs spend time with people who use the product, and for reporting that includes dealership operators who rely on these screens daily.
• Lean and dense: small team with high talent density and AI augmentation; hiring is focused on multiplying leverage rather than filling org charts.
• Direct exposure: you report to the Staff PM for Data, CDP and Analytics, collaborate with CPBO, VP of Product, VP of Engineering, and data platform and reporting leads, and present to the executive team.