Data Engineer

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.
• Familiarity with B2B SaaS metrics, including ARR, pipeline, conversion, retention, churn, and expansion.
• Ability to translate ambiguous business requirements into scalable technical solutions.
• Strong communication skills and experience partnering directly with nontechnical stakeholders.

Compensation & Benefits

• We offer a competitive and thoughtfully structured compensation package designed to align with impact, experience, and long-term growth.
• Base Salary: The anticipated salary range for this role is $200,000 - $260,000, depending on experience, skills, scope, and location.
• Bonus: This role is Bonus eligible and may participate in the Company's discretionary annual bonus program.
• Equity: In addition to cash compensation, employees are eligible to participate in the company’s stock option program and share in Higgsfield’s long-term growth.
• Benefits: We offer a comprehensive benefits package designed to support employees professionally and personally, including medical, dental, and vision insurance, a competitive 401(k) retirement plan with company matching, and additional benefits and perks.
• The opportunity to work on ambitious AI products alongside a highly experienced, fast-moving, and international team.
• Significant ownership, direct impact, and opportunities for professional growth as the company scales.

This is a hybrid role based in the San Francisco Bay Area. Team members are expected to work from our San Francisco office three full days per week, with the remaining days worked remotely and are expected to be available during agreed working hours and to maintain sufficient overlap with the relevant team’s time zone. We value in-person collaboration, active communication, responsiveness, and close partnership across teams.