Founding Data Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Salary

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401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Company stage

Series A From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Founding Data Engineer San Francisco Bay Area, San Francisco, California, USA About Higgsfield Higgsfield AI is the leading video AI company redefining synthetic media on socials. The company is entering its next stage of scale with $200M+ run-rate sales in just 9 months after launch, and a fresh $130M Series A. Who we are looking for Everyone at Higgsfield is an A-player. You are: - A strong SQL and data modeling expert who cares deeply about metric integrity. - Obsessed with building reliable, auditable systems, not just dashboards. - Comfortable bringing structure to fast-moving, ambiguous environments. - An excellent communicator who can clearly explain complex metric logic to engineering, product, ML, growth, and finance. - Motivated by company-wide impact and ownership, not just local optimizations. This role reports into the VP of Finance but partners closely with every function. The ideal candidate is based in the San Francisco Bay Area and able to come in person 2 days a week. What you will work on Own the Source of Truth - Translate product- and finance-defined metrics (engagement, MRR, CAC, LTV, margins, etc.) into durable, version-controlled warehouse models (dbt or equivalent), ensuring consistent usage across the company. - Eliminate conflicting logic across dashboards and teams. - Ensure executive- and board-level reporting is powered by consistent, traceable warehouse logic. Build Guardrails - Mature our existing BigQuery-based stack by centralizing business logic in the warehouse and enforcing governance controls. - Implement automated validation and reconciliation between product systems, billing systems, and financial reporting.

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