Director, Data Analytics

Poshmark

Director of Data Analytics leading analytics infrastructure for Poshmark's revenue team. Building data-driven decision frameworks across merchandising, growth, and supply strategy.

Posted 7/23/2026full-timeRedwood City • California • 🇺🇸 United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in building and managing analytics infrastructure to drive data-driven decision-making, with proficiency in SQL, Python, and advanced dashboarding tools. Strong leadership skills in mentoring analysts and collaborating with cross-functional teams to translate complex data into actionable insights.

Highest-signal resume keywords

SQL ProficiencyPython ProgrammingAnalytics Infrastructure DevelopmentDashboard and Visualization SkillsTeam Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalyticsStatistical AnalysisData ManipulationData TransformationFunnel AnalyticsSupply/Demand ModelingBehavioral Event DataProject ManagementRevenue AnalysisCommercial Strategy

Soft Skills

Effective CommunicationStorytelling with DataCross-Functional CollaborationMentoringProject Management

Tools & Technologies

DatabricksSnowflakeLookerTableauDbtGenAI ToolsLLMs

Certifications & Qualifications

Bachelor's Degree in Quantitative FieldMaster's Degree in Quantitative Field

Industry Keywords

E-CommerceConsumer MarketplaceFashionRetailRevenue Intelligence

Tech Stack

Tools & technologies

PythonSQLTableau

About the role

Key responsibilities & impact

Own the end-to-end analytics stack for the Revenue team, defining what data we need, how it connects, and how it surfaces as a single source of truth across demand signals, inventory health, sell-through, and seller GMV opportunity.
Translate search acceleration, save behavior, sell-through rates, and category liquidity into a live picture of platform health. Identify where supply is failing to meet demand and build the framework that matches buyer intent to seller opportunity.
Build continuous systems that surface which trends are accelerating, where supply gaps are forming, and where early sourcing is needed, packaging these into actionable briefs that let Supply Partnerships and Merchandising move before a GMV window closes.
Build operational dashboards for the CRO and Revenue leadership that answer specific business questions daily, and own their ongoing quality, accuracy, and evolution.
Integrate GenAI tools into daily workflows to accelerate output, and architect toward a Revenue Intelligence Platform where demand sensing, campaign performance, and seller opportunity are surfaced automatically and continuously.
Serve as the analytical backbone for Merchandising, Growth, Supply Partnerships, and Product. Partner with Data Engineering to productionize frameworks. Hire, mentor, and grow a team of analysts and promote a data-driven culture across the Revenue org.

Requirements

What you’ll need

8–12 years in data analytics, with meaningful time spent in consumer marketplace, e-commerce, fashion, or retail environments.
Proven track record of building analytics infrastructure that changed how a business makes decisions not just reported on decisions already made.
Experience working directly with senior commercial leadership and translating business strategy into data architecture.
Demonstrated experience leading or growing a team of analysts; strong senior individual contributors will be considered for the right candidate.
Bachelor's or Master's degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics) or equivalent practical experience.
Expert-level proficiency in SQL. Strong programming skills in Python for data manipulation, statistical analysis, and pipeline automation.
Hands-on experience in Databricks, Snowflake, or equivalent large-scale data environments.
Experience with dbt or similar data transformation frameworks and modern data stack tooling.
Advanced dashboard and visualization skills proficient in Looker, Tableau, or equivalent; knows the difference between a report and a decision surface.
Familiarity with behavioral event data, funnel analytics, and supply/demand modeling in a two-sided marketplace context.
Practical, hands-on experience using LLMs (e.g., Claude, Gemini, ChatGPT) to write and optimize queries, troubleshoot code, and accelerate analytics workflows.
Commercial instincts to match technical fluency understands how sell-through rate, inventory liquidity, trend velocity, and supply gaps connect to revenue outcomes.
Proven ability to translate complex data into actionable business recommendations and communicate effectively with non-technical stakeholders.
Strong project management skills; able to manage multiple workstreams across cross-functional partners simultaneously.
Ability to tell a story with data and drive executive alignment on analytical findings and infrastructure investment.

Benefits

Comp & perks

Paid time off
Professional development opportunities