About this role.
Updater is seeking a Lead Data Analyst to own product-performance measurement across consumer, marketplace, embedded-commerce, and AI-powered product lines. The role centers on defining KPIs, building trusted Looker dashboards, analyzing funnels, and designing statistically rigorous A/B tests. This analyst will build dbt models in Snowflake, size roadmap opportunities, monitor product health, and deliver recurring reporting for enterprise partners. The position requires 5+ years of product analytics experience, expert SQL, strong stakeholder management, and comfort operating independently in ambiguous, high-visibility situations.
Role DNA
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Job Complexity
4/5Pace & Pressure
4/5Autonomy Level
5/5Communication Load
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Core skills
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Cover letter sample
Dear Hiring Team,
I am excited to apply for the Lead Data Analyst, Product Analytics role at Updater. My background in product analytics, SQL, experimentation, and funnel optimization aligns strongly with the opportunity to turn complex behavioral data into clear product and business decisions.
I would bring a rigorous, stakeholder-oriented approach to defining trusted KPIs, building scalable dashboards and data models, and explaining the drivers behind changes in conversion and engagement. I am particularly drawn to Updater's multi-sided marketplace environment and its investment in AI-powered consumer experiences.
I would welcome the opportunity to help product, marketing, and customer-success teams prioritize high-impact opportunities and make faster, evidence-based decisions. Thank you for your consideration.
Sample interview questions
I would first validate that the decline is real by checking data freshness, instrumentation changes, metric definitions, and dashboard logic. I would then segment the funnel by product line, acquisition source, device, geography where applicable, cohort, and step-to-step progression to isolate where the drop occurred. Finally, I would combine quantitative findings with release, marketing, and operational timelines to form and test likely causes, communicating both confidence levels and recommended actions.
I would define the primary conversion metric, guardrail metrics, eligible population, randomization unit, and the expected minimum detectable effect before launch. I would estimate sample size and duration using baseline conversion, desired power, and significance thresholds, while ensuring exposure is assigned consistently. After launch, I would monitor sample-ratio mismatch and guardrails, then report the effect size, uncertainty interval, segment results, and a clear recommendation rather than relying only on a p-value.
I would begin with documented metric definitions, ownership, source-of-truth tables, and agreed business logic. Dashboards should emphasize decision-relevant KPIs, show trends and comparisons clearly, include sensible drill-down paths, and use automated freshness and quality checks. I would also review dashboards regularly with stakeholders so the reporting evolves with product strategy rather than becoming a static collection of charts.
I would start by defining canonical event, user, session, and conversion grain, then create tested staging models that standardize source fields and event semantics. I would build intermediate models for reusable journey logic and a clearly documented mart with stable dimensions, KPI definitions, and incremental processing where appropriate. I would add dbt tests for uniqueness, relationships, accepted values, and freshness, and partner with analysts to ensure the model answers common questions without duplicating logic.
I would lead with the decision-relevant conclusion, the magnitude of impact, and my confidence in the result. I would explain the most important evidence and caveats in plain language, distinguish facts from hypotheses, and show the operational or product implications. I would close with concrete next steps, such as validating a suspected cause, pausing a rollout, or prioritizing a targeted experiment.
Do you love turning messy behavioral data into the “aha” that changes a product roadmap? Do you want your dashboards to be the first thing product leaders open in the morning — and your analyses to inform what gets built next? If so, we want to talk to you!
About the Role
Updater operates at the intersection of embedded commerce, consumer marketplaces, and AI-powered buyflows. Millions of consumers use our products to find and purchase internet, utilities, insurance, moving services, and more — and every click, invite, and order tells a story. The story involves difficult consumer choices, understanding what product fits their needs. On the other side of the marketplace there’s also provider complexity about what consumers represent good credit risks. Your job is to find both sides of the story and make changes actionable.
As our Lead Data Analyst for Product Analytics, you’ll own how we measure product performance across Updater’s product lines — from our consumer Moving App and Pro Onboarding for multifamily residents, to PoweredBy embedded commerce and our Marketplace, to our newest AI agentic experiences. You’ll build the reporting that tracks our most important KPIs — funnel conversion, order rate, claim rate, engagement — and go beyond the “what” to explain the “why,” shaping experiments and roadmaps along the way.
This is a high-visibility, high-ownership seat. You’ll partner directly with multiple product teams, along with marketing, and customer success. Your insights will inform decisions from feature design to executive strategy. We’re also aggressively leaning into AI: we’ve been developing LLM-based agentic experiences that help consumers purchase complex products with confidence, and our data teams use Claude Code and other LLM-based tools daily to move faster and dig deeper. If you’re excited to practice analytics at the frontier, you’ll be at home here.
What You’ll Own
- KPI reporting & dashboards — Define, build, and maintain the Looker dashboards that track funnel conversion and key product KPIs across product lines, so every team shares one trusted view of performance.
- Product performance analysis — Investigate user behavior across the full journey (invite → onboarding → active usage → conversion) to explain why metrics move and where the biggest opportunities hide.
- Experimentation — Design and analyze A/B tests that are statistically sound and trusted for business decisions, partnering with product and marketing to raise conversion across our buyflows.
- Data modeling — Build and maintain dbt models in Snowflake that power self-serve analytics and keep metric definitions consistent and reliable.
- Roadmap planning & impact sizing — Size opportunities and quantify the impact of launches so product teams invest in the highest-leverage work.
- Partner & external reporting — Own recurring performance reporting for key enterprise partners, in collaboration with customer success.
- Incident support & ad hoc insights — Monitor product health, help spot anomalies before they hit the business, and answer high-stakes questions with fast, rigorous analysis.
What Success Looks Like
- Every product line has clearly defined KPIs with dashboards stakeholders trust — even when the numbers are uncomfortable.
- When funnel conversion moves, we know why within hours, not weeks.
- Product roadmaps are informed by your opportunity sizing and experiment results.
- A/B tests across the company are statistically fair and consistently interpreted.
- Partner-facing reports ship accurately and on time, every time.
About You
- Product sense: you think like a designer and a strategist — you see the opportunity behind the metric, not just the metric.
- Comfort with ambiguity: you consistently deliver results from open-ended questions, without waiting for a perfectly scoped ticket.
- Strong communication: you tailor your message to your audience, whether that’s an executive, an engineer, or a non-technical partner.
- Relationship builder: you proactively build trust with stakeholders who don’t speak SQL.
- 5+ years of experience in product analytics, data analysis, or a similar role
- Expert SQL and strong experience with modern analytics warehouses (Snowflake, BigQuery, Redshift)
- Hands-on experience designing, instrumenting, and analyzing A/B tests with sound statistical rigor
- Experience building dashboards and self-serve reporting in a BI tool (Looker strongly preferred, experience with Fullstory a plus)
- Deep familiarity with funnel analysis, conversion metrics, and user journey analytics
Bonus Points For
- Experience with dbt and analytics engineering workflows
- Python (or similar) for analysis and automation
- Experience in marketplaces, embedded commerce, affiliate, or other multi-party revenue environments
- Experience using LLM-based tools to accelerate analytical work
Compensation
This posting is anticipated to remain open until 8/28/2026. The new hire salary range for this position is $150,000 – $180,000 annually. Factors which may affect the starting pay within this range include skills, experience, and other qualifications aligned with Updater’s internal leveling guidelines.
About Updater
Updater is a leading technology platform helping major brands acquire and retain customers at scale. We are on a mission to power millions of complex transactions through intelligent, autonomous systems. By combining deep integrations, real-world data, and purpose-built AI agents, we’re transforming fragmented purchasing workflows into seamless, automated experiences – freeing businesses and consumers from operational friction and enabling a new standard of speed, accuracy, and scale.
Updater has raised over $450 million from leading investors, including SoftBank Capital, Vista Credit Partners, IA Ventures, Commerce Ventures, Second Century Ventures (the strategic investment arm of the National Association of Realtors®), and more. For more information, please visit www.updater.com.
Updater is proud to be an equal opportunity employer and will consider all qualified applicants regardless of color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital or family status, disability, gender identity or expression, veteran status, actual or presumed belonging to an ethnic group, or any other legally protected status. If you have a disability or special need that requires accommodation, please let us know.
Benefits: The Company offers the following benefits for full-time positions, subject to applicable eligibility requirements:
- Medical, Dental, and Vision Insurance
- Flexible PTO
- 13 paid company holidays annually
- Updater Stock Options
- 401(k) with employer match
- Wellbeing Subsidy
- One Medical membership
- Virtual on-demand healthcare through Teladoc and Talkspace
- Flexible spending account (FSA)
- Health savings account (HSA)
- Supplemental Short & Long Term Disability Insurance
- Supplemental Life Insurance
- Paid Parental Leave
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