Head of Data Engineering
New
E
EveLegal Technology
Remote - USFull-TimeManager
Salary280,000 - 350,000 USD per year
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Job Details
- Required Skills
- SQLETLSnowflakeAirflowData engineeringData modelingSaaSBigQuerydbtRedshift
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.
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.
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