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Harvey

Senior Analytics Engineer, Product

Harvey

Senior Analytics Engineer focusing on Product to design data models that power decision-making at Harvey. Collaborating with cross-functional teams to deliver actionable insights.

Posted 5/25/2026full-timeSan Francisco • California • 🇺🇸 United StatesSenior💰 $155,800 - $233,600 per yearWebsite

Tech Stack

Tools & technologies
PythonSQL

About the role

Key responsibilities & impact
  • Design and build scalable data models and pipelines using dbt to transform raw data into clean, reliable assets that power company-wide analytics and decision-making.
  • Define and implement a robust semantic layer (e.g. LookML/Omni/Other) that standardizes key business metrics, dimensions, and data products, ensuring self-serve capabilities for stakeholders across teams.
  • Partner cross-functionally with Product, GTM, Finance, and the Exec Team to deliver intuitive, consistent dashboards and analytical tools that surface business health metrics.
  • Establish and champion data modeling standards and best practices, guiding the organization in how to model data for accuracy, performance, usability, and long-term maintainability.
  • Partner with Product Managers, Engineers, and Data teams to design tracking plans for new product surfaces, ensuring events are implemented accurately, consistently, and with downstream analytics use cases in mind.
  • Own the product event tracking strategy, including event naming conventions, property schemas, identity resolution, sessionization, versioning, deprecation, and documentation standards.
  • Empower stakeholders with data by making analytical assets easily discoverable, reliable, and well-documented – turning complex datasets into actionable insights for the business.
  • You’ll define the structure, taxonomy, governance, and modeling patterns for product event data, ensuring that user behavior, product usage, and customer journeys are captured consistently from instrumentation through analytics-ready models.

Requirements

What you’ll need
  • 5+ years of experience in Analytics Engineering, Data Engineering, Data Science, or similar field.
  • Deep expertise in SQL, dbt, Python, Snowflake.
  • Experience with modern BI tools like (Looker/Omni, or similar).
  • Skilled at defining core business and product metrics, uncovering insights, and resolving data inconsistencies across complex systems.
  • Strong familiarity with version control (GitHub), CI/CD, and modern development workflows.
  • Bias for action – you prefer launching usable, iterative data models that deliver immediate value over waiting for perfect solutions.
  • Strong communicator who can build trusted partnerships across Product, GTM, Finance, and Exec stakeholders.**Comfortable working through ambiguity in fast-moving, cross-functional environments.
  • Balances big-picture thinking with precision in execution – knowing when to sweat the details and when to move quickly.
  • Experience modeling high-volume, semi-structured product event data, including JSON payloads, nested properties, user/account identifiers, sessions, funnels, cohorts, and behavioral metrics.
  • Experience with product analytics tools (Mixpanel, Segment, Amplitude)

Benefits

Comp & perks
  • Comprehensive health, dental and vision coverage
  • Retirement benefits (401k match up to 4%)
  • Flexible PTO
  • Equity plan and benefits program

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools
SQLdbtPythonSnowflakeLookerOmniGitHubCI/CDdata modelingproduct analytics
Soft Skills
strong communicatorbuilding trusted partnershipsbias for actionworking through ambiguitybig-picture thinkingprecision in execution