Job description

About Vehlo: We started Vehlo in 2019 with a simple goal: to be the industry’s favorite provider of repair shop technology. Across every part of the auto repair industry, Vehlo is igniting vehicle service success with software and financial solutions that unlock your potential. Our founder-led products power the entire service lane experience and keep customers coming back with streamlined tools that help you handle communication, workflow automation, touchless payments, valet pickup, and much more. We’re out to simplify the customer journey from start to finish and give power back to the people under the hood, making their jobs easier and your shop more profitable —just ask our over 30,000 customers, who generate more than 60M annual repair orders, and process over $12B in payments volume annually. At Vehlo, our only purpose is your success, and together, we’re reaching your goals faster than ever. Being a Veep comes with more than a comprehensive benefits package—our biggest benefit is opportunity: Opportunity to make an impact, opportunity for growth, and opportunity for recognition and rewards. This is not a mega-corporation where you wonder what people are doing all day - every Veep is moving the ball forward day in, day out for our customers or for each other. About This Role: We're looking for a Principal Product Manager to own our customer-facing data, analytics and insights portfolio end to end. Most of our customers buy more than one Vehlo product and then cobble together other solutions to assemble the 360-degree view of their business that we don't yet give them natively. Closing that gap is the starting point, but the bigger opportunity is what we build on top of it. We're not looking for someone to ship more dashboards. More value will come from AI-powered insights that tell an operator what's happening in their business and what to do about it, without them having to know what to ask. At Vehlo, a Principal Product role is senior, highly visible, and hands-on, reporting to the SVP of Product. You won't have direct reports on day one, but that could change as we grow the business. You'll own strategy and set the pace of play while leading through partners in engineering, analytics, customer success and go-to-market. You'll drive the commercial model as well as the product: what it costs us to serve, what belongs in which tier, and what customers pay for. What You'll Do: • New AI-powered insight products, built zero to one: surfacing what an operator would never have thought to ask, explaining why a number moved, predicting what's coming, and recommending the next action, delivered inside the workflow rather than in a separate analytics destination. • The premium analytics product line end to end: reporting and dashboard experiences, alerting, natural-language reporting, and meaningful additions to the basic reporting built into individual products. • The cross-product view: one unified analytics experience spanning a customer's entire Vehlo footprint. • Data delivery beyond the dashboard: APIs, MCP surfaces, exports, warehouse sharing, BI connectors, and the access model that governs which customer sees which data. • The semantic layer and the metric definitions inside it, across products that were built separately and don't yet agree with each other. • Pricing, packaging, and unit economics: cost-to-serve per location, what's free because it drives retention, and what's genuinely a paid tier. • Aggregate benchmarking and market-intelligence products built from our repair data, along with the data-rights and aggregation model that makes them defensible. • Data quality and customer trust as measured product outcomes, so we reinforce trust and value in the market. In your first 90 days • Align the teams on a governance model so everyone knows what every number in our analytics product means and where it comes from. • Build a cost-to-serve model per location that our finance team accepts. • Meet customers across the full size range and come back with a point of view on what the unified view has to do. • Publish the product strategy: what belongs in the base product, what belongs in a premium tier, what we stop doing, and your first candidates for net-new AI-powered products, with the reasoning behind them. What You'll Need: • 7+ years in product management, including at least 2 years specifically in B2B SaaS data products, reporting, or analytics. • Demonstrated ownership of customer-facing analytics: reporting, dashboards, or embedded analytics that paying customers relied on. Internal BI and executive reporting are a different discipline and won't prepare you for this. • Experience building analytics that span more than one product or module, rather than a reporting tab attached to a single application. • Ownership of a semantic or metric layer across multiple source systems, including the judgment calls when two teams defined the same metric differently in production. • Experience serving both ends of a wide customer range: the very small owner/operator business that will never hire an analyst, and the large sophisticated customer with its own data team, without shipping two disconnected products. • A zero-to-one track record: you've identified an opportunity, validated it, and shipped a product that didn't exist before, not only improved a mature one. • Commercial instinct with evidence: you've priced or packaged an analytics capability, built a cost-to-serve model, or owned a revenue number for a data product. • Enough technical depth to read a schema, write SQL, and evaluate an API contract without waiting to be told whether something is feasible. That said, we're not looking for you to write production code. • Fluency in the unit economics of analytics. • Genuine enthusiasm for the data work itself: modeling it, making it trustworthy, and turning it into decisions customers rely on every day. • Hands-on working style and fluency with AI tooling: you prototype, pull your own data, and use AI to move faster than a product manager could a few years ago. Preferred Qualifications (Optional): • Experience shipping AI-driven product surfaces to customers, including how you handled accuracy, evaluation, user trust, and being wrong in front of a customer. • You've created public-facing benchmarking or aggregate market-intelligence products that are referenced by the industry. • Usage-based or consumption pricing, and cost attribution per customer. • Experience running customer-facing analytics alongside a small analytics engineering team rather than a large data platform organization. Note: This job description is intended to outline the general responsibilities and requirements of the role. It is not an exhaustive list of all duties, tasks, or responsibilities that may be required. Responsibilities and priorities may evolve over time, and the company reserves the right to make changes at any time with or without notice. Vehlo is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws. This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. Vehlo makes hiring decisions based solely on qualifications, merit, and business needs at the time.

Requirements

Must-haves

The premium analytics product line end to end: reporting and dashboard experiences, alerting, natural-language reporting, and meaningful additions to the basic reporting built into individual products.
The cross-product view: one unified analytics experience spanning a customer's entire Vehlo footprint.
Data delivery beyond the dashboard: APIs, MCP surfaces, exports, warehouse sharing, BI connectors, and the access model that governs which customer sees which data.
The semantic layer and the metric definitions inside it, across products that were built separately and don't yet agree with each other.
Pricing, packaging, and unit economics: cost-to-serve per location, what's free because it drives retention, and what's genuinely a paid tier.
Aggregate benchmarking and market-intelligence products built from our repair data, along with the data-rights and aggregation model that makes them defensible.
Data quality and customer trust as measured product outcomes, so we reinforce trust and value in the market.
In your first 90 days
Align the teams on a governance model so everyone knows what every number in our analytics product means and where it comes from.
Build a cost-to-serve model per location that our finance team accepts.
Meet customers across the full size range and come back with a point of view on what the unified view has to do.
Publish the product strategy: what belongs in the base product, what belongs in a premium tier, what we stop doing, and your first candidates for net-new AI-powered products, with the reasoning behind them.
7+ years in product management, including at least 2 years specifically in B2B SaaS data products, reporting, or analytics.
Experience building analytics that span more than one product or module, rather than a reporting tab attached to a single application.
Ownership of a semantic or metric layer across multiple source systems, including the judgment calls when two teams defined the same metric differently in production.
A zero-to-one track record: you've identified an opportunity, validated it, and shipped a product that didn't exist before, not only improved a mature one.
Commercial instinct with evidence: you've priced or packaged an analytics capability, built a cost-to-serve model, or owned a revenue number for a data product.
Enough technical depth to read a schema, write SQL, and evaluate an API contract without waiting to be told whether something is feasible. That said, we're not looking for you to write production code.
Fluency in the unit economics of analytics.
Genuine enthusiasm for the data work itself: modeling it, making it trustworthy, and turning it into decisions customers rely on every day.
Hands-on working style and fluency with AI tooling: you prototype, pull your own data, and use AI to move faster than a product manager could a few years ago.
Experience shipping AI-driven product surfaces to customers, including how you handled accuracy, evaluation, user trust, and being wrong in front of a customer.
You've created public-facing benchmarking or aggregate market-intelligence products that are referenced by the industry.
Usage-based or consumption pricing, and cost attribution per customer.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aigosqlapi

Platform: paycom
Effort: medium