Senior Analytics Engineer

Salary: $170K - $200K Employment Type: Full-Time

Position Overview

Harvey is a secure AI platform for legal and professional services that augments productivity and automates complex workflows. We utilize custom-developed algorithms with reasoning-adept LLMs, built by our expert team of lawyers, engineers, and research scientists. We have achieved product-market fit and are rapidly scaling our team.

Why Harvey?

• Exceptional Product Market Fit: Partnered with the largest law firms and professional service providers globally, including Paul Weiss, A&O Shearman, Ashurst, O'Melveny & Myers, PwC, KKR, and many others.
• Strategic Investors: Raised over $500 million from leading investors such as Sequoia, Google Ventures, Kleiner Perkins, and OpenAI.
• World-Class Team: Hiring top talent from DeepMind, Google Brain, Stripe, FAIR, Tesla Autopilot, Glean, Superhuman, Figma, and more.
• Partnerships: Direct collaboration with OpenAI to build the future of generative AI and redefine professional services.
• Performance: Achieved 4x ARR in 2024.
• Competitive Compensation: Offering competitive compensation packages.

Role Overview

We are seeking a versatile Senior Analytics Engineer to architect the data backbone that powers decision-making at Harvey. With proven product-market fit and surging demand, you will design clean, reliable pipelines and semantic data models to transform raw events into actionable insights. As the first Analytics Engineer, you will select and implement the data stack, champion best practices in testing and documentation, and collaborate closely with Product, Go-To-Market (GTM), and leadership to empower every team with confident data-driven decision-making. If you combine engineering rigor with a passion for data storytelling and want to shape analytics from the ground up, we encourage you to apply.

Responsibilities

• 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.
• Partner cross-functionally with Product, GTM, Finance, and the Executive 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 data modeling 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 for data warehouse reliability and performance.
• 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, transforming complex datasets into actionable business insights.

Requirements

• 5+ years of experience in Analytics Engineering, Data Engineering, Data Science, or a similar field.
• Deep expertise in SQL, dbt, and Python.
• Proficiency with modern BI/semantic layer tools such as 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.
• A bias for action – preference for launching usable, iterative data models that deliver immediate value over waiting for perfect solutions.
• Strong communication skills with the ability to build trusted partnerships across Product, GTM, Finance, and Executive stakeholders.
• Comfortable working through ambiguity in fast-moving, cross-functional environments.
• Ability to balance big-picture thinking with precision in execution.