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Wagmo · 6 hours ago

Lead Data Analyst

NYC Metro Area

Full-time

Hybrid

Senior Level, Lead/Staff

$150K/yr - $180K/yr

7+ years exp

Wagmo is a new type of pet health company focused on empowering responsible pet parenting through innovative pet benefits. The Lead Data Analyst will spearhead the data strategy, transforming data into actionable insights to enhance revenue and operational efficiency while collaborating across multiple teams to define key metrics and drive data-driven growth.

B2CInsurancePet

Responsibilities

Data strategy, modeling, and analytics engineering leadership: Own the company’s analytics foundation and metric architecture. Set the technical and analytical direction for how data is modeled, governed, and consumed across the business. Translate ambiguous, high-impact questions into scalable data products and clear metric definitions. Establish and evolve robust dbt models/semantic layers in BigQuery, with strong standards for performance, maintainability, and discoverability. Drive best practices across dbt/SQL/Git, including testing strategy (schema/uniqueness/relationships), CI/CD, code review norms, backfill strategy, and long-term data model roadmaps

Own executive-ready reporting. Lead the design and delivery of executive-ready reporting and business performance narratives. Own the KPI layer and reporting system that powers weekly business reviews, monthly close, OKRs, and board materials. Ensure reporting is trusted, consistent, and decision-grade through strong QA standards, reconciliation processes, and clear documentation. Drive adoption by enabling self-serve analytics, training stakeholders on metric interpretation, and improving data literacy across Finance, Sales, Marketing, Product, and Operations

Lead growth & revenue analytics. Serve as the analytics lead for growth and revenue strategy. Own end-to-end funnel measurement and insights across acquisition, conversion, retention, expansion, and margin. Proactively identify trends and opportunities, size impact, and partner with leaders to prioritize initiatives based on quantified ROI. Establish experimentation and measurement best practices, ensuring teams can evaluate performance and make fast, evidence-based decisions

Cross-functional influence and storyteller. Act as a key business partner to Finance and functional leaders, shaping strategy through crisp, compelling analysis. Communicate complex topics clearly across technical and non-technical audiences. Build narratives and visualizations that align stakeholders, clarify trade-offs, and drive action—especially in ambiguous, fast-moving environments

Operationalize insights. Move beyond dashboards by embedding metrics and alerts into day-to-day operations. Partner with Sales, Marketing, Product/Engineering, Customer Operations, Strategic Partnerships, and Client Success to design workflows and playbooks that convert signals into action (e.g., churn risk, lead quality, claims processing insights, margin anomalies). Define the operating model for how teams respond to metrics, including ownership, escalation paths, and success measurement

Data quality, governance and trust at scale. Establish and lead data quality and governance standards across the company. Define SLAs for freshness/accuracy, anomaly detection, and issue triage. Maintain a business glossary, metric registry, and dashboard QA standards to prevent metric drift. Align analytics practices with privacy/compliance requirements. Build a culture of accountability and trust in data by making definitions, lineage, and decision logic transparent and easy to understand

Qualification

SQLDbtBigQueryAnalytics engineeringTableauGitSaaS metricsCross-functional leadershipCommunication skillsOrganizational skillsTime management

Required

8+ years in analytics/BI/analytics engineering, ideally in high-growth SaaS/consumer tech, with a track record of leading company-critical analytics initiatives (growth, revenue, margin, operational efficiency) from ambiguous problem to measurable business impact

Demonstrated ownership of the analytics roadmap and delivery of decision-grade insights used in exec/board contexts

Expert-level analytics engineering and data modeling leadership: deep SQL and dimensional/semantic modeling expertise; extensive dbt experience on BigQuery (or similar); strong Git/CI/CD and production-grade engineering practices

Able to define team standards for testing, data contracts, performance optimization, backfills, and documentation—and raise the quality bar for the org's data foundation

Exec-ready reporting system ownership: proven ability to design and maintain the KPI layer and reporting ecosystem that powers WBRs, monthly close, OKRs, and board materials

Experienced in metric definition governance, reconciliation, QA, and ensuring reporting is consistent, explainable, and trusted across teams

Strategic, cross-functional leadership and influence: skilled at aligning Finance, Sales, Marketing, Product/Engineering, Ops, and Client Success on shared definitions, priorities, and trade-offs

Able to drive decisions without authority, build stakeholder trust, and lead through conflict to a clear outcome

Strong business and growth analytics depth: fluency in SaaS metrics and unit economics (LTV/CAC, payback, retention/cohorts, pipeline, conversion, expansion), experimentation, and causal thinking

Can size opportunities, forecast impact, and recommend actions with clear assumptions and sensitivity analysis

Turns ambiguity into scalable metrics + decision frameworks: repeatedly translates unclear questions into durable metric definitions, self-serve models, and repeatable analyses that move KPIs

Creates clarity across teams by codifying definitions, lineage, and 'how we measure' into documentation and governance

High ownership in fast-moving environments, with leverage: operates autonomously, but at L4 level also creates leverage for others—through prioritization frameworks, stakeholder operating rhythms, standardized tooling, and enablement

Comfortable making calls under uncertainty, sequencing work for maximum impact, and improving processes as the company scales

7+ years in data analytics, business intelligence, or data engineering (ideally in high-growth SaaS/consumer tech), with a track record of owning SQL/dbt pipelines, building executive-ready dashboards, and turning business questions into decision-grade insights

Advanced SQL; modeling with dbt on BigQuery (or similar); Git workflows; strong visualization instincts (Tableau or analogous BI)

Proven track record of working autonomously with strong organizational, prioritization, and time management skills

Preference for experience in start-ups or fast-growing, scaling companies

Clear, direct communicator able to frame trade-offs, persuade with data, and align cross-functional stakeholders

Experience partnering with Client Success, Sales & Marketing, Operations, Product/Engineering, Finance

Fluency in SaaS metrics (LTV/CAC, payback, retention/cohorting, pipeline), experimentation, and unit economics

Track record turning ambiguous questions into clear metrics, analyses, and decision-ready recommendations that move KPIs

Organized, autonomous, and comfortable operating in a fast-moving, high-ownership environment