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Founding Data Engineer

Broccoli AI broccoli.com Open · verified Oct 24, 2026
On-site San Francisco Full-time Mid-level Data Engineering

At a glance

Mid-level Data Engineering role at Broccoli AI. San Francisco · full-time · $180,000–$230,000 base.

SalaryStated by Broccoli AI
$180,000 – $230,000
Base salary for this role, in USD per year, as published in the posting.
This role, from Broccoli AIOur estimate for the market: $181,250–$299,375Median $211,250
The range includes the market median of $211,250 for mid-level data engineering roles in San Francisco.
Worked out from 22 postings that stated pay, median $211,250. Last updated Oct 13, 2026.
RoleData Engineering
SeniorityMid-level
LocationSan Francisco
WorkplaceOn-site
EmploymentFull-time
Base pay$180,000–$230,000
PostedAug 18, 2026 · 2mo ago
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Build and operate ingestion pipelines that move data from every source into ClickHouse, choosing the tools and managing the flow
  • Shape raw feeds into documented tables and link records so each customer is consistent across billing, support and call data
  • Create shared canonical views and metric definitions for dashboards and analysis, then make them usable by people and AI agents
  • Add freshness checks, quality tests and alerts, and investigate pipeline failures before customers encounter them
  • Analyze segments and partner questions, while coordinating with engineering on schemas, events and architecture changes

What you bring

  • At least four years in data or analytics engineering, including responsibility for production pipelines from ingestion through operation
  • Strong SQL and Python, plus practical experience with ETL tools and orchestration
  • Experience with a columnar or OLAP warehouse such as ClickHouse, BigQuery, Snowflake or Redshift
  • A track record of designing data models and tables that others use, with care for what the metrics represent

Who this fits

This suits a mid-level data engineer ready to be the first dedicated data hire, own architecture and tooling decisions, and work closely with Strategy & Ops and engineering. The role is onsite in San Francisco.

From the employer

About Broccoli

At Broccoli, we're building AI teammates for the people who build and maintain our world.

We partner with plumbing, HVAC, and electrical contractors, the hardworking businesses that keep homes and communities running, and replace fragmented software and repetitive manual work with AI that actually gets the job done.

Our AI teammates answer phones, book appointments, follow up with customers, recover missed revenue, and help contractors deliver exceptional customer experiences, all while integrating seamlessly with platforms like ServiceTitan.

Before we wrote a single line of code, we visited more than 140 contractors to understand how these businesses truly operate. That firsthand experience shaped everything we've built.

Today:

  • Hundreds of contractors rely on Broccoli every day.

  • We've grown to $15M+ ARR in under two years.

  • We're trusted by everyone from independent contractors to some of the largest private equity backed operators in the home services industry.

  • We're backed by Khosla Ventures and Y Combinator.

We're still just getting started.

About the role

Our data is rich and comes from many sources. Every customer dashboard, every business review, every metric the company runs on draws from it — and we haven't yet built the unified data layer that makes all of that fast, consistent, and ready to scale.

You'll build that layer and own it. You'll model our data into clean, documented tables and build the source-of-truth library and own the data definitions the whole team runs on. You'll work hand in hand with the Strategy & Ops team — and essentially every tool we build, especially the external-facing dashboards and analytics our customers see, will be built on your work.

You're the team's first dedicated data hire: you own the architecture, the tooling choices, and the trust in every number. What you build powers customer-facing dashboards, cross-customer benchmarks, and eventually the business intelligence we ship inside the product.

What you'll do

  • Build and run the pipelines. Reliable ingestion from all our sources into ClickHouse — you choose the tooling and own the flow.

  • Model the data. Turn raw feeds into clean, documented tables — including entity resolution, so a customer is the same customer across billing, support, and call data.

  • Build the source-of-truth library. Canonical views and metric definitions that every dashboard and analysis reads from.

  • Make the data Human & AI-ready. Structure our models, definitions, and documentation so both people and AI agents can query them and get the right answer — then build the internal tools that let anyone at Broccoli ask a data question and trust the response.

  • Keep it trustworthy. Freshness checks, quality tests, and alerts — we find out a pipeline broke before a customer does.

  • Run deep dives when the team needs them. Ad-hoc analyses, segment investigations, partner questions.

  • Work closely with engineering. Understand how our systems store and produce data, including schemas, events, and architecture, and give input early on changes so the data that lands in the warehouse is usable, stable, and easy to model.

What we're looking for

  • 4–8+ years in data or analytics engineering — you've built and operated production pipelines end to end, and been the one paged when they broke.

  • Strong SQL and solid Python; hands-on with ETL tooling (Airbyte, Fivetran, Dagster, dbt, or hand-rolled) and orchestration.

  • Real experience with a columnar/OLAP warehouse — ClickHouse ideally; BigQuery, Snowflake, or Redshift transfer fine.

  • Data modeling as a craft: you've designed the tables other people query, and you care what the numbers mean, not just that the pipes run.

Nice to have

  • Self-directed: you've been the first or only data person somewhere, or built a data platform from scratch

  • ClickHouse specifically — materialized views, performance tuning on event-scale data.

  • Multi-source identity / entity resolution experience.

  • Exposure to customer-facing or multi-tenant analytics (strict customer-level data isolation).

  • B2B SaaS operational data — calls, bookings, jobs, billing — or CRM/field-service data like ServiceTitan.

Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Engineering$180k+

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.