Senior Analytics Engineer, Product
$156k - $234k • Remote • San Francisco • FullTime
Posted 1d ago
About the job
Harvey is transforming legal and professional services by combining agentic AI, an enterprise-grade platform, and deep domain expertise. We are seeking a versatile Senior Analytics Engineer focusing on Product to architect event data models that power decision-making. You will design clean, reliable pipelines and semantic data models that turn raw events into usable insights, helping to evolve our data stack and champion best practices. This role is ideal for someone who combines engineering rigor with a love for storytelling through data, and wants to build a generational company at a true inflection point.
Responsibilities
- Design and build scalable data models and pipelines using dbt to transform raw data into clean, reliable assets.
- Define and implement a robust semantic layer to standardize key business metrics and ensure self-serve capabilities.
- Partner cross-functionally with Product, GTM, Finance, and Exec teams to deliver intuitive dashboards and analytical tools.
- Establish and champion data modeling standards and best practices for accuracy, performance, and maintainability.
- Partner with Product Managers, Engineers, and Data teams to design tracking plans for new product surfaces.
- Own the product event tracking strategy, including naming conventions, schemas, identity resolution, and documentation.
- Empower stakeholders with data by making analytical assets discoverable, reliable, and well-documented.
- Define the structure, taxonomy, governance, and modeling patterns for product event data.
Requirements
- 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 and resolving data inconsistencies.
- Strong familiarity with version control (GitHub), CI/CD, and modern development workflows.
- Bias for action, preferring iterative data models that deliver immediate value.
- Strong communicator capable of building trusted partnerships across teams.
- Comfortable working through ambiguity in fast-moving, cross-functional environments.
- Balances big-picture thinking with precision in execution.
- Experience modeling high-volume, semi-structured product event data, including JSON payloads, nested properties, and behavioral metrics.
- Experience with product analytics tools (Mixpanel, Segment, Amplitude).