About the job
About Higgsfield AI
Higgsfield AI is at the forefront of video artificial intelligence, transforming the landscape of synthetic media for social platforms. With an impressive trajectory, our company has achieved over $200 million in run-rate sales just nine months post-launch and secured a robust $130 million Series A funding round.
Who We Are Seeking
At Higgsfield AI, we strive for excellence, and we are looking for top-tier talent. You are:
A proficient SQL and data modeling specialist who prioritizes metric integrity.
Passionate about constructing reliable, auditable systems beyond mere dashboards.
Skilled at imposing structure within fast-paced and ambiguous settings.
An outstanding communicator capable of articulating complex metric logic to various teams including engineering, product management, machine learning, growth, and finance.
Driven by the desire to create a company-wide impact and ownership, rather than focusing solely on localized optimizations.
This position reports to the VP of Finance and collaborates closely with all departments. The ideal candidate will be located in the San Francisco Bay Area and will be required to work in the office at least two days a week.
Your Responsibilities
Establish the Source of Truth
Transform product and finance-defined metrics (like engagement, MRR, CAC, LTV, margins, etc.) into sustainable, version-controlled warehouse models (using dbt or similar), ensuring uniform application throughout the company.
Resolve conflicting logic across dashboards and teams.
Guarantee that executive and board-level reports are based on consistent and traceable warehouse logic.
Create Guardrails
Enhance our existing BigQuery-based infrastructure by centralizing business logic in the warehouse and enforcing governance protocols.
Deploy automated validation and reconciliation processes between product systems, billing systems, and financial reporting.
Avert unnoticed metric drift and unexpected post-close discrepancies.
Ensure that new products, models, and features are accurately reflected in reporting.
Empower the Organization
Collaborate with Product, Engineering, ML, Growth, and Finance teams to provide trustworthy, decision-ready data.
Enhance documentation, testing, and transparency within the warehouse.
Minimize key-person risk while improving overall knowledge sharing.

