Data Analyst, Product and Growth

About Noovo

Noovo is transforming the van life experience through thoughtful design, comfort, and craftsmanship. Headquartered in Las Vegas, the company builds premium vans on a premium chassis with European-inspired interiors, creating vehicles that feel like home on the road. It is one of the fastest-growing lifestyle vehicle brands in the U.S., with a modern look, a transparent buying journey, and a genuine community of travelers who embrace a different way to live.

Role Overview

Noovo is hiring a Data Analyst focused on Product and Growth to take ownership of how the business measures, interprets, and acts on digital performance. This is the first analytics role dedicated to the digital product team, giving you the chance to establish the analytics function from the ground up. The role is centered on building reliable reporting, clear funnel and KPI definitions, and actionable insights that support product and leadership decisions, including reporting in HubSpot. You will act as the analytical partner who identifies what the business should know, even when no one has asked yet.

This is a strategic analytics role rather than a basic data-piping job. You will be responsible for the full measurement lifecycle, from defining and validating how data is captured to shaping executive dashboards. You will work closely with product, engineering, marketing, and sales, serving as the business’s single trusted source for performance reporting.

Key Responsibilities

• Design the event taxonomy and measurement framework the business needs, then work with engineering and consulting support to verify that the data is accurate and dependable.
• Spot data quality problems that undermine current reporting and reset baselines once fixes have been confirmed.
• Maintain tracking integrity across the website so teams can trust the numbers they use.
• Build and update the KPI tree, including the leading and lagging indicators for every stage of the funnel from first visit to lead creation.
• Create precise definitions for funnel stages, including the distinction between a true digital lead and a lower-intent inquiry.
• Keep the funnel model grounded in real lead quality so reported volumes reflect genuine prospects rather than inflated totals.
• Own dashboards covering visit-to-lead-to-sale performance for the product team, marketing channel performance, and a streamlined executive view for leadership.
• Develop a single reporting source so the organization can work from one system with self-service filtering by date, channel, and segment.
• Improve HubSpot reporting and ensure lifecycle stages, lead tracking, and channel metrics remain accurate.
• Treat calls, boutique visits, RV show interactions, and other offline touchpoints as important conversion events so every lead source is visible.
• Link online and offline activity across web, phone, and events to identify which sources truly generate qualified leads and deposits.
• Highlight the channels that are performing best so spend and effort can be allocated based on evidence.
• Spend time proactively exploring the data to uncover insights the business has not yet requested.
• Convert analysis into prioritization guidance so roadmap and marketing choices are informed by evidence instead of instinct.
• Work with product, marketing, and sales to answer ad hoc questions and challenge assumptions, such as cancellation rates, deposit-intent thresholds, and conversion by segment.
• Explain findings clearly in plain language for non-technical audiences, including leadership.

Technical Knowledge

• GA4 and Google Tag Manager
• Event taxonomy design
• Behavioral and session analytics tools such as Hotjar
• HubSpot reporting, lifecycle setup, and funnel configuration
• SQL and data querying
• Cloud data warehouses, preferably Google BigQuery
• BI and dashboard tools such as Looker Studio, with transferable experience from Looker, Tableau, or Power BI
• Multi-touch attribution modeling
• Funnel and conversion analysis
• Data validation and quality assurance
• AI and automation

Qualifications

The ideal candidate brings 3 to 6 years of experience in a data analyst, product analyst, marketing analyst, or growth analytics role. You should have hands-on experience with web instrumentation and event taxonomy design using tools such as GA4 and tag management, plus comfort collaborating with engineering on server-side tracking.

Strong experience with HubSpot reporting is required, along with a practical understanding of lead lifecycle and funnel stages. You should be proficient in SQL and at least one BI or dashboarding platform, and comfortable working with a cloud data warehouse, especially BigQuery. The role also calls for a proven ability to define metrics and build a KPI tree or similar measurement structure from scratch.

You should be able to investigate ambiguous questions, connect analytics work to business outcomes, and communicate complex data clearly to non-technical teammates and leadership. Comfort with ambiguity and the ability to work independently in a fast-moving environment are important.

Preferred Qualifications

• Experience with attribution modeling across both online and offline channels.
• Experience in DTC, e-commerce, or a high-consideration, high-ticket purchasing funnel.
• Experience building self-service reporting for leadership.
• Exposure to experimentation and A/B testing.
• Experience in a startup or fast-growing company.
• A background that connects product analytics with marketing or revenue analytics.
• Experience working in Google Cloud Platform (GCP).
• Exposure to dbt or ELT tools such as Airbyte or Fivetran, while pipeline building is handled by a dedicated resource.

Compensation and Benefits

• Medical, dental, and vision coverage
• Paid time off and company holidays
• 401(k) plan
• Opportunity for growth within a rapidly expanding, design-led company

Location

This position is remote.