Job Overview
Location
San Francisco
Job Type
Full-time
Category
Data Science
Date Posted
May 26, 2026
Full Job Description
đź“‹ Description
- • Design and build scalable data models and pipelines using dbt to transform raw event data into clean, reliable analytics assets that power company-wide decision-making.
- • Define and implement a robust semantic layer using Looker, Omni, or similar tools to standardize key business metrics, dimensions, and data products for self-serve analytics across teams.
- • Partner with Product, GTM, Finance, and Executive leadership to deliver intuitive, consistent dashboards and analytical tools that surface critical business health metrics.
- • Establish and champion data modeling standards and best practices for accuracy, performance, usability, and long-term maintainability across the organization.
- • Collaborate with Product Managers and Engineers to design tracking plans for new product features, ensuring accurate, consistent implementation of events with downstream analytics in mind.
- • Own the product event tracking strategy, including event naming conventions, property schemas, identity resolution, sessionization, versioning, deprecation, and comprehensive documentation standards.
- • Structure, taxonomy, governance, and modeling patterns for product event data to ensure consistent capture of user behavior, product usage, and customer journeys from instrumentation to analytics-ready models.
- • Empower cross-functional stakeholders by making analytical assets easily discoverable, reliable, and well-documented, turning complex datasets into actionable business insights.
- • Work with high-volume, semi-structured product event data including JSON payloads, nested properties, user/account identifiers, sessions, funnels, cohorts, and behavioral metrics.
- • Utilize version control (GitHub), CI/CD workflows, and modern development practices to maintain data pipeline integrity and collaboration efficiency.
- • Communicate effectively with non-technical stakeholders to translate data insights into strategic recommendations and build trusted partnerships across Product, GTM, Finance, and Exec teams.
- • Balance big-picture strategic thinking with precision in execution, knowing when to iterate quickly and when to refine details for long-term scalability.
- • Apply bias for action by launching usable, iterative data models that deliver immediate business value over waiting for perfect solutions in fast-moving environments.
🎯 Requirements
- • 5+ years of experience in Analytics Engineering, Data Engineering, Data Science, or similar field.
- • Deep expertise in SQL, dbt, Python, and Snowflake.
- • Experience with modern BI tools such as Looker, Omni, or similar.
- • Experience modeling high-volume, semi-structured product event data including JSON payloads, user identifiers, sessions, funnels, and cohorts.
- • Strong familiarity with version control (GitHub), CI/CD, and modern development workflows.
- • Experience with product analytics tools such as Mixpanel, Segment, or Amplitude.
🏖️ Benefits
- • Compensation range of $155,000 - $235,000 USD depending on location.
- • Opportunity to join a hyper-growth startup at a critical inflection point with world-class investor support.
- • Work alongside a team that values Decisiveness, Simplicity, and Job's Not Finished.
- • Access to a fast-scaling company with 1500+ customers in 60+ countries.
- • Exposure to frontier agentic AI and enterprise-grade product platforms shaping the future of professional services.
- • Equal opportunity employer committed to reasonable accommodations for applicants with disabilities.
Skills & Technologies
About Harvey AI Inc.
Harvey AI Inc. provides a generative artificial-intelligence platform engineered specifically for the legal profession. The software integrates with law-firm workflows to automate contract drafting, review, due-diligence and regulatory research, producing lawyer-quality language grounded in up-to-date statutes and precedents. Harvey combines large language models trained on legal corpora with secure, private-cloud deployment and firm-specific fine-tuning to maintain confidentiality and compliance. Clients range from global law firms to in-house legal departments seeking efficiency gains without compromising accuracy or security. The company was founded in 2022 and is headquartered in San Francisco, California.
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