Lead Data Engineer

Eve is a company redefining legal technology for plaintiff law firms, focusing on building AI solutions that enhance case management. The Lead Data Engineer will design and build the data warehouse architecture, develop ETL/ELT pipelines, and establish data quality practices to support business operations and insights.

Responsibilities:

• 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

Requirements:

• 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