Data Engineer

About the role

Why work at Higgsfield AI?

Higgsfield AI is the fastest-scaling generative AI company in history, hitting $1B in annual revenue run rate, 30M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands.

We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like.

About the role:

We're looking for a Data Engineer, B2B & GTM to build and scale the data infrastructure powering Higgsfield's enterprise business and go-to-market operations.

This role will own the development of reliable data pipelines, integrations, and data models that connect our product usage, customer, sales, and revenue data. You'll work closely with Sales, Revenue Operations, Finance, and Product to establish a trusted foundation for reporting, forecasting, customer intelligence, and strategic decision-making.

This is a hands-on engineering role with significant ownership and the opportunity to build scalable data systems in a rapidly growing B2B business.

What you'll do:

- Design, develop, and maintain scalable data pipelines integrating CRM, billing, product analytics, and other business-critical systems.

- Connect product usage, account activity, sales pipeline, contracts, and revenue data to create a consistent view of B2B customers.

- Build reliable, well-documented data models supporting pipeline analytics, revenue reporting, customer segmentation, retention, and expansion.

- Partner with Sales, RevOps, and Finance to support forecasting, territory planning, account prioritization, sales performance, and revenue attribution.

- Establish visibility into how enterprise customers adopt and use Higgsfield's products, enabling insights into conversion, engagement, and expansion opportunities.

- Implement automated validation, monitoring, documentation, and governance to ensure data accuracy and consistency across systems.

- Identify opportunities to improve pipeline performance, automation, and infrastructure as the business grows.

Requirements:

- 6-8+ years of experience in Data Engineering, Analytics Engineering, or a closely related technical role.

- Strong proficiency in SQL and Python, with experience building production-grade ETL/ELT pipelines.

- Experience working with modern data warehouses such as Snowflake, BigQuery, or Redshift.

- Hands-on experience with data transformation and orchestration tools such as dbt, Airflow, Dagster, or similar technologies.

- Experience integrating data from business systems such as Salesforce, HubSpot, Stripe, or other CRM and billing platforms.

- Strong understanding of data modeling, data architecture, and data quality best practices.