Staff Analytics Engineer, Harvey
$200-250k
Offers equity and bonus
3 days a week in office
Domain-specific AI for legal and professional services
Open for applications
Domain-specific AI for legal and professional services
501-1000 employees
Open for applications
$200-250k
Offers equity and bonus
3 days a week in office
501-1000 employees
Company mission
To help professionals develop expertise, faster.
Role
Who you are
- If you combine engineering rigor with a love of storytelling through data and want to shape analytics from the ground up, we’d love to meet you
- 7+ years of experience in Analytics Engineering, Data Engineering, or Data Science
- Deep expertise in SQL, dbt, Python, and modern BI/semantic layer tools like Looker or Omni
- 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 operating in a B2B or commercial setting, with an understanding of customer lifecycle and revenue-driving metrics
What the job involves
- We’re looking for a Staff Analytics Engineer to architect the data backbone that powers decision-making at Harvey
- With product-market fit already proven and demand surging across diverse customer segments, you’ll design clean, reliable pipelines and semantic data models that turn raw events into immediately usable insights
- As the founding Analytics Engineer on our team, you’ll choose and implement the right data stack, champion best practices in testing and documentation, and collaborate closely with product, GTM, and leadership to ensure every team can answer its own questions with confidence
- 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) 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 real-time business health metrics
- Establish and champion data modeling standards and best practices, guiding the organization in how to model data for accuracy, usability, and long-term maintainability
- Collaborate with engineering to make key decisions on data architecture, co-design data schemas, and implement orchestration strategies that ensure reliability and performance of the data warehouse
- Lead data governance initiatives, ensuring high standards of data quality, consistency, documentation, and access control across the analytics ecosystem
- Empower stakeholders with data by making analytical assets easily discoverable, reliable, and well-documented—turning complex datasets into actionable insights for the business
Our take
The explosive popularity of generative AI tools has seen specialized solutions popping up for all kinds of industries. Hoping to help supercharge efficiency and productivity for legal teams, Harvey supplies generative AI that can assist with documentation, as well as aid research and optimize workflows.
Via natural language instructions, Harvey helps draft and analyze legal documents. It can also answer complex questions across large document sets, or even handle research queries that cover multiple domains in legal, regulatory and tax.
Its ability to support legal practitioners as if it's another member of the team is what makes Harvey particularly interesting. This approach has seen the company raise substantial funding, reaching Unicorn status in 2024. Funds are now being used to expand to new geographies, grow headcount and further collect and curate data to train more “domain-specific” AI models.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 9 rounds)
Oct 2025
$160m
LATE VC
Oct 2025
$59m
GROWTH EQUITY VC
Total funding: $1.0bn
Company HQ
Financial District, San Francisco, CA
Leadership
Winston Weinberg
(Co-Founder & CEO)Graduated with a Juris Doctor from the USC Gould School of Law, then spent 1 year as an Associate at O'Melveny & Myers before founding Harvey.
Gabe Pereyra
(Co-Founder & President)Previously worked as a Research Scientist at Meta and DeepMind. Also spent a year as a Brain Resident at Google.
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