3 months ago
Base Salary
$156k - $234k/yr
Responsibilities
- Design and build scalable dbt data models and pipelines that transform raw data into reliable analytics assets.
- Define and implement a semantic layer using tools such as LookML or Omni to standardize metrics, dimensions, and data products.
- Partner with Product, GTM, Finance, and executive stakeholders to deliver consistent dashboards and analytical tools.
- Establish data modeling standards and best practices for accuracy, performance, usability, and maintainability.
- Design product tracking plans and ensure events are implemented consistently for downstream analytics use cases.
- Own product event tracking strategy, including naming conventions, property schemas, identity resolution, sessionization, versioning, deprecation, and documentation.
- Make analytical assets discoverable, reliable, and well documented for self-serve stakeholder use.
- Define taxonomy, governance, and modeling patterns for product event data covering user behavior, product usage, and customer journeys.
Requirements
- 5+ years of experience in Analytics Engineering, Data Engineering, Data Science, or a similar field.
- Deep expertise in SQL, dbt, Python, and Snowflake.
- Experience with modern BI tools such as Looker, Omni, or similar.
- Ability to define business and product metrics, uncover insights, and resolve data inconsistencies across complex systems.
- Familiarity with GitHub, CI/CD, and modern development workflows.
- Experience modeling high-volume, semi-structured product event data, including JSON payloads, nested properties, identifiers, sessions, funnels, cohorts, and behavioral metrics.
- Experience with product analytics tools such as Mixpanel, Segment, or Amplitude.
- Strong communication and cross-functional collaboration skills, including with Product, GTM, Finance, and executive stakeholders.
- Experience with data engineering and managing data warehouses, preferably Snowflake, is a bonus.
- Experience with AI and LLMs, early-stage hyper-growth startups, or world-class enterprise organizations is a bonus.
About Harvey
Harvey builds domain-specific generative AI for legal and other professional services, delivered as an enterprise platform and APIs to automate contract analysis, due diligence, compliance, and litigation workflows. Founded in 2022 and headquartered in San Francisco, it sells to law firms and corporate legal departments on enterprise agreements; investors include Sequoia Capital and OpenAI. Customers include multiple Am Law 100 firms and Fortune 500 companies’ legal teams.