---
title: 'Data Automation Specialist at Harper'
canonical: 'https://feeny.ai/job/data-automation-specialist-harper-san-francisco-dng49ww48npf'
type: 'job'
last_seen: '2026-09-12'
---

# Data Automation Specialist at Harper

- **Company:** Harper
- **Location:** San Francisco, CA
- **Compensation:** $120k–$160k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-06-22
- **Last confirmed live:** 2026-09-12
- **Apply:** https://jobs.ashbyhq.com/harperinsure/5997b504-ac32-4651-863c-7619e35567b6

## Job description

Data Automation Specialist

Harper is an AI-native commercial insurance company in San Francisco. We're not bolting AI onto insurance — we're rebuilding the entire business as software, on a simple bet: turning expert human judgment into compute is one of the largest transitions left to make, and a trillion-dollar industry still run 90% by hand is the place to prove it. We've grown ~100x in the last year and we move at that speed — on-site, in person, long days, very high standards. Almost no one joins Harper for insurance; they join to build the company that replaces how it works.

## The role

Data is only valuable if people can use it — and most teams can't, because the gap between raw data and actionable signal is filled with manual work nobody has time for. You close that gap. You build the automations, agents, and AI-powered workflows that take the outputs of Harper's data systems and make them legible, timely, and immediately actionable for everyone on the team. You'll spend real time in AI tools — building agents, designing prompts, orchestrating workflows — and you treat automation not as a nice-to-have but as the only way to scale a high-velocity growth operation.

You're a builder who lives at the intersection of data, AI, and automation. You're not a data engineer building pipelines from scratch, and you're not a data analyst running queries — you're the person who takes what's already flowing and makes it work for the humans who need it. You're fluent in AI tools and modern automation platforms, comfortable writing code when the situation calls for it, and you have a builder's instinct for the workflows that should never require human effort. You report to the Head of Marketing and collaborate across the GTM, growth, and operations teams. Winning in 6–12 months looks like the whole team moving faster because you built the systems that remove friction from data at every step.

## What you'll do

- Build data automations. Design and implement automated workflows that surface insights, trigger alerts, and route information to the right people at the right time — without anyone having to ask.
- Develop AI agents. Use modern AI tooling to build agents that monitor, summarize, and interpret data outputs, cutting the manual work required to turn data into action.
- Create operational dashboards and feeds. Build lightweight, automated reporting that gives the team an always-current view of performance — no manual refresh required.
- Identify and eliminate manual data work. Audit how the team interacts with data today, find the repetitive manual steps, and replace them with automated systems.
- Maintain and improve automation infrastructure. Own the reliability and performance of what you build, and iterate as data systems and team needs evolve.
- Partner with the data and growth teams. Work closely with the GTM Engineer and Data Analyst to understand what data exists and where automation adds the most leverage.

## Who you are

- You've built automations that genuinely changed how a team operates — not just connected two tools together.
- You're fluent in at least one major AI development environment and have built real agents or AI-powered workflows, not just prototypes.
- You have a builder's instinct: when you see a manual process, your first thought is how to eliminate it.
- You're comfortable writing Python or working with APIs when no-code tools reach their limits.
- You think about the end user of every automation you build — not just whether it works, but whether it's actually useful.
- You can move from idea to working prototype quickly, and you know when to polish and when to ship.
- You're based in San Francisco or willing to relocate.

The reality — read this before you apply

This is a builder's seat, measured by how much faster you make the team — not by automations shipped or tools connected. It's on-site in San Francisco, in person, long days, high standards. The data systems and team needs keep changing underneath you, which means the automations you own have to keep working, and when one breaks or goes stale, that's yours to find and fix — usually the same day. You'll work open-ended problems with little spec, so the job is as much judgment about what's worth automating as it is the building itself.

This isn't a place to wire up integrations no one uses, and it isn't a pipeline-engineering or pure-analyst role. Almost no one takes it for insurance — they take it because building the AI-powered automation layer for a company growing ~100x, where automation is a real competitive advantage, is a rare seat. If making a team measurably faster is the appeal, apply. If it's a deterrent, it won't get easier here.

## Compensation & logistics

- Salary: $120,000–$160,000, plus performance bonus and equity.
- Location: On-site, San Francisco. Based here or willing to relocate.
- Schedule: Monday–Friday, long days, in the building with the team.

## Benefits

- Uber commuter benefits
- Meals provided — breakfast, lunch, and dinner
- Snacks, drinks, and coffee stocked daily
- Free gym membership
- Health, dental, and vision insurance

## Requirements

- 3+ years of experience in automation, data operations, or a technical marketing/growth operations role
- Hands-on experience building workflows in automation platforms (Zapier, Make, n8n, or comparable)
- Demonstrated experience building with AI tools and LLM APIs to create agents, summaries, or AI-powered workflows
- Working knowledge of Python or another scripting language for tasks that require custom logic
- Familiarity with data outputs from marketing and analytics platforms; comfortable reading and transforming structured data
- Strong problem-solving instincts and the ability to work autonomously on open-ended technical challenges

## Nice to have

- Experience building agents using modern AI frameworks (LangChain, CrewAI, or comparable)
- Background working alongside data engineers or analysts to understand and extend data pipelines
- Familiarity with marketing analytics stacks and GTM data flows
- Experience with prompt engineering and workflow design for LLM-based systems
- Exposure to a high-growth startup environment where automation was a competitive advantage

Process

- People screen — fit and alignment
- Lead screen — skills and judgment
- Super day — how you operate in real time

To apply

Send your resume and a description of an automation or AI agent you built — the problem it solved, and how you built it.

## About Harper

## Company Overview

- **One-liner**: Harper is an AI-native commercial insurance brokerage that uses data and automation to help mid-sized businesses secure optimal coverage faster and at lower cost.
- **Entity Type**: Private startup (Y Combinator Winter 2025, raised $47 million)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2024
- **Founders**: Dakotah Rice (CEO) and Tushar Nair (CTO)

## Core Business

- Primary industry: Commercial insurance (Excess & Surplus lines brokerage)
- Target customers: Mid-sized businesses with complex insurance needs, spanning technology, life sciences, aerospace, construction, and consulting
- Mission: "We want to become the largest insurance brokerage in the world with the best NPS." (Source: [Y Combinator](https://www.ycombinator.com/companies/harper))

## Products & Services

- **Harper Hub**: Proprietary AI-native platform that automates form filling, carrier matching, and client communications, cutting weeks from the traditional quoting timeline.
- **Brokerage Services**: Comprehensive commercial insurance products including General Liability, Professional Liability (tech E&O with no AI exclusions), Cyber Insurance, Commercial Auto, Commercial Property, Umbrella, and Bonds – all placed through an AI-enhanced workflow.
- **Specialty Expertise**: Deep coverage for regulated industries such as FDA‑regulated labs, aerospace contractors, and security guard firms.

## Market Standing

- **Valuation / Market Cap**: Not publicly disclosed
- **Key Metric**: Total funding of **$47 million** (confirmed on company website and Y Combinator profile; some third‑party sources list a lower figure but official sources indicate $47M)
- **Notable Investors**: Y Combinator (pre‑seed lead); other investors not publicly detailed
- **Growth Signals**: Writing over **$6 million in annualized premiums** across 35 states (as of early 2025); **6,000+ clients** with **98.78% client retention**; headcount of 39 employees growing **353% year‑over‑year**; **19 open positions**; 100% success placing tech E&O without AI exclusions.

## Competitive Advantages

- **AI‑native infrastructure**: Proprietary technology automates quoting, binding, and service, enabling faster turnaround and lower overhead compared to traditional brokers.
- **Deep niche expertise**: Focus on complex, regulated industries (tech, life sciences, aerospace) where incumbents often struggle.
- **High retention**: 98.78% client retention rate and proven ability to place hard‑to‑cover policies (e.g., tech E&O with AI exclusions) signal strong customer trust.
- **Data‑driven underwriting**: Real‑time analysis of prior interactions and quote intelligence to match businesses with the best carrier.

## Strategic Focus

- Scaling the AI‑native brokerage to serve the mid‑market today and eventually all businesses (commercial insurance commissions represent a $100B+ market).
- Aggressively hiring across engineering, sales, operations, and partnerships to support rapid growth.
- Expanding carrier partnerships and geographic reach (currently licensed in 35 states).

## Why Work Here

- **Early‑stage impact**: Join a Y Combinator‑backed startup at its inflection point, building the AI‑native future of insurance.
- **High‑leverage roles**: Engineers and GTM professionals work directly on systems (LLMs, automation) that drive measurable business outcomes.
- **Culture**: "Human expertise amplified by AI" – domain knowledge meets cutting‑edge technology; teammates from Goldman Sachs, Coinbase, and other top firms.
- **Work environment**: San Francisco headquarters with both in‑office and remote roles available depending on the position.
- **Compensation**: Competitive startup salaries (e.g., $160K–$230K for engineering roles per job listings).
- **Career growth**: Fast‑growing company (353% headcount growth) with opportunities to shape processes and take on ownership early.

## Sources

1. [harperinsure.com](https://harperinsure.com/) – Company website (home page)
2. [jobs.ashbyhq.com/harperinsure](https://jobs.ashbyhq.com/harperinsure) – Careers page
3. [ycombinator.com/companies/harper](https://www.ycombinator.com/companies/harper) – Y Combinator company profile
4. [linkedin.com/company/harperinsure](https://www.linkedin.com/company/harperinsure) – LinkedIn company page
5. [builtin.com/company/harper-harperinsurecom](https://builtin.com/company/harper-harperinsurecom) – Built In company profile

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