Lead Data Engineer

Company Overview: At Eve, we’re redefining what’s possible in legal technology. Our mission is to empower plaintiff law firms with AI-driven solutions that elevate how they operate, serve clients, and grow. We believe the future of law will be built by “AI-Native Law Firms” — firms that are managed, scaled, and optimized by intelligent systems rather than manual processes and endless administrative work. Eve’s technology augments the capabilities of attorneys across every stage of a case — from intake and document review to strategy and settlement — so they can focus on what truly matters: achieving the best outcomes for their clients. Our vision is simple yet transformative: enable every firm to operate at its highest potential through the power of AI. Why Join Eve Product-market fit: Eve is used by over 550+ law firms, and we’re growing fast. Backed by top investors: We’ve raised over $160M from world-class partners including Spark Capital, Andreessen Horowitz(A16z), Menlo Ventures, and Lightspeed. Built by a world-class team: Engineers, designers, and operators from places like Scale, Meta, Airbnb, Cruise, Square, Rubrik, and Lyft are building Eve from the ground up. AI-Native from day one: We’re on the bleeding edge of AI, collaborating directly with teams at OpenAI and Anthropic to build best-in-class AI workflows tailored for legal work. Explosive growth: We are growing 2X revenue Quarter over Quarter. The Opportunity We’re hiring Eve's 1st Leader of Data Engineering to build the foundation that turns Eve into a truly data-driven company. This is a builder role. You’ll architect and own the company’s data infrastructure from the ground up, turning fragmented data into reliable systems that teams can trust and build on, then build a team to help Eve continue to scale. What You'll Do

Design and build Eve’s data warehouse architecture from the ground up, including schema design, data modeling, and pipeline orchestration.

Develop and maintain reliable ETL/ELT pipelines that integrate data across core business systems (CRM, product, billing, marketing, etc.).

Define and implement core business data models that standardize how Eve measures pipeline, conversion, revenue, customer health, and attribution.

Build a reliable GTM data layer that enables marketing, sales, CS, and finance teams to self-serve key insights without ad hoc analysis.

Establish data quality, governance, and monitoring practices to ensure accuracy and reliability across the data stack.

Create cross-functional intake and prioritization processes for data requests, balancing infrastructure work with business needs.

Partner closely with GTM, finance, product, and engineering teams to understand their workflows and translate them into durable data systems.

Select and manage Eve’s data stack (warehouse, orchestration, transformation, BI tooling).

Lay the foundation for product analytics and behavioral event tracking across Eve’s platform.

Build and scale Eve’s data function over time, including hiring, team structure, and operating processes.

What You'll Bring

Proven experience building a data warehouse and core data infrastructure from scratch at a high-growth SaaS or technology company.

Deep expertise in data engineering, including data modeling, ETL/ELT pipeline design, and warehouse architecture.

Strong proficiency with SQL and modern data stack tools (e.g., Snowflake/BigQuery/Redshift, dbt, Airflow/Prefect, etc.).

Experience integrating and modeling data from GTM systems such as CRM, marketing automation, billing, and customer success platforms.

Demonstrated ability to translate business workflows into durable data models that teams can rely on for decision-making.

Comfortable operating in early-stage environments with messy, incomplete, or inconsistent data.

Strong cross-functional communication skills and ability to work closely with sales, marketing, CS, finance, and product teams.

Experience owning architectural decisions for the data stack, including tooling selection and infrastructure design.

Familiarity with product analytics and event instrumentation across web or application platforms.

Fluency with AI-assisted development tools such as Cursor, Claude Code, or GitHub Copilot.

Entrepreneurial mindset with a desire to build and own a data function from the ground up.