Description
We are looking for a versatile Senior Analytics Engineer to partner closely with our Finance team in building the financial data foundation that drives decision-making at Harvey.
Compensation
- $155K – $235K
- Offers Equity
- Offers Bonus
Additionally, this role is eligible to participate in our equity plan and benefits program. Benefits include, but are not limited to: Comprehensive health, dental and vision coverage, retirement benefits (401k match up to 4%), and flexible PTO.
Why Harvey
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
Role Overview
We’re looking for a versatile Senior Analytics Engineer to partner closely with our Finance team in building the financial data foundation that drives 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 source data into usable insights.
What You'll Do
- Design and build scalable data models and pipelines using dbt to transform raw data into clean, reliable assets that power company-wide financial analytics and decision-making.
- Define and implement a robust semantic layer that standardizes financial and operating metrics, including revenue, retention, customer growth, usage, margin, and forecast inputs.
- Partner cross-functionally with Product, Finance, and the Exec Team to deliver intuitive, consistent dashboards and analytical tools that surface business health metrics.
- Establish and champion data modeling standards and best practices, guiding the organization in how to model data for accuracy, performance, usability, and long-term maintainability.
- Lead data governance initiatives, ensuring high standards of data quality, consistency, documentation, and access control across the analytics ecosystem.
- Structure financial metric definitions, business logic, and accounting context in ways that can support AI-assisted reporting, natural language analytics, and automated anomaly detection.
What You Have
- 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.
- Skilled at defining core financial and operating metrics, uncovering insights, and resolving data inconsistencies across complex systems.
- Strong familiarity with version control, 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 Finance, GTM, Product, 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 modeling financial, billing, subscription, CRM, or usage-based revenue data.
- Strong understanding of business metrics such as ARR, MRR, churn, retention, expansion, bookings, billings, and revenue recognition.
Bonus
- Early employee at a hyper-growth startup
- Experience with or knowledge of AI and LLMs
- Data Engineering Experience
- Experience managing data warehouse
- Experience at world-class enterprise orgs