Founding Data Engineer at Higgsfield AI
About the Role
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.
Prevent silent metric drift and post-close surprises.
Ensure new products, models, and features are correctly integrated into reporting.
Enable the Company
Partner with Product, Engineering, ML, Growth, and Finance to deliver trusted, decision-ready data.
Improve documentation, testing, and transparency across the warehouse.
Reduce key-person risk and increase confidence in company metrics.
What you bring
5-10+ years in analytics engineering, data engineering, or similar role owning business-critical datasets.
Expert-level SQL and strong experience with transformation frameworks (e.g., dbt or equivalent).
Experience supporting revenue or financial reporting in a high-growth company.
Proven ability to reconcile product/billing data with financial systems.
Experience implementing warehouse-level testing, validation, and governance.
Strong written and verbal communication skills.
Experience in a fast-growing startup environment.