Founding Data Analytics Engineer

Broccoli AI • San Francisco, CA

3d

About The Position

Broccoli is seeking a Founding Data Analytics Engineer to build and own the unified data layer for the company. This role is crucial for making data fast, consistent, and scalable, supporting customer dashboards, business intelligence, and internal analytics. The data engineer will be responsible for modeling data into clean, documented tables, establishing the source-of-truth library, and owning data definitions. This position will work closely with the Strategy & Ops team and engineering to ensure data quality and usability, powering customer-facing analytics and internal BI tools. As the first dedicated data hire, this individual will own the data architecture, tooling choices, and ensure the trustworthiness of all company data.

Requirements

• 4–8+ years in data or analytics engineering experience.
• Proven experience building and operating production data pipelines end-to-end.
• Strong SQL and solid Python skills.
• Hands-on experience with ETL tooling such as Airbyte, Fivetran, Dagster, dbt, or custom solutions.
• Experience with orchestration tools.
• Real experience with a columnar/OLAP warehouse (ClickHouse ideally; BigQuery, Snowflake, or Redshift are acceptable).
• Proficiency in data modeling, designing tables for others to query, and understanding the meaning of data.
• Experience being the one paged when production pipelines break.

Nice To Haves

• Self-directed experience, having been the first or only data person in a company or built a data platform from scratch.
• Specific experience with ClickHouse, including materialized views and performance tuning on event-scale data.
• Experience with multi-source identity or entity resolution.
• Exposure to customer-facing or multi-tenant analytics, with a focus on strict customer-level data isolation.
• Experience with B2B SaaS operational data (calls, bookings, jobs, billing) or CRM/field-service data like ServiceTitan.

Responsibilities

• Build and run reliable data ingestion pipelines from all sources into ClickHouse, choosing appropriate tooling and owning the entire flow.
• Model raw data feeds into clean, documented tables, including entity resolution to ensure consistent customer data across different systems.
• Build a source-of-truth library with canonical views and metric definitions for all dashboards and analyses.
• Structure data models, definitions, and documentation to be accessible and usable by both humans and AI agents, enabling trustworthy data querying.
• Implement freshness checks, quality tests, and alerts to proactively identify and resolve pipeline issues before they impact customers.
• Perform ad-hoc analyses, segment investigations, and address partner data requests.
• Collaborate closely with the engineering team to understand data production systems, schemas, events, and architecture, providing input to ensure data usability and stability in the warehouse.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed