Head of Data Engineering

About Eve

Eve is redefining legal technology for plaintiff law firms, and we're building the team that will take us there. We help firms handle more cases, recover more for clients, and grow with AI that works across every stage of a case, from intake through resolution. The next generation of great plaintiff firms will be AI-Native, and Eve is how they get there. But what makes Eve different isn't just the product. It's how we build it. If you're someone who takes ownership, stays curious, and wants to build AI that's already changing how law is practiced, this is where you belong.

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 We're Looking For:

• 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