Data Engineer

Higgsfield AI; San Francisco (CA); Hybrid; USD 200,000 - 260,000; Full time

Benefits offered by this job

Stock options

Medical, dental, and vision insurance

401(k) with company match

Growth opportunities

Job summary

Higgsfield AI is hiring a Data Engineer for hybrid work in the San Francisco Bay Area to build and scale data infrastructure for B2B and go-to-market operations.

Responsibilities include designing scalable data pipelines that integrate CRM, billing, product analytics, and other critical systems, connecting data across sales, contracts, and revenue, and building well-documented data models for analytics and reporting.

Qualifications

• 6+ years of experience in Data Engineering or Analytics Engineering.
• Proficient in SQL and Python for production-grade ETL/ELT pipelines.
• Experience with modern data warehouses (Snowflake/BigQuery/Redshift).
• Hands-on with data transformation/orchestration tools (dbt, Airflow, Dagster).
• Experience integrating Salesforce, HubSpot, Stripe, and other CRMs/billing platforms.
• Strong data modeling, architecture, and data quality practices.
• Familiarity with ARR, pipeline, conversion, retention metrics in B2B SaaS.
• Ability to translate ambiguous business needs into scalable solutions.

Responsibilities

• Design, develop, and maintain scalable data pipelines that integrate CRM, billing, product analytics, and other business-critical systems.
• Connect product usage, account activity, sales pipeline, contracts, and revenue data to deliver a consistent view of B2B customers.
• Build data models that are reliable and well-documented for pipeline analytics, revenue reporting, customer segmentation, and retention and expansion insights.
• Collaborate with Sales, RevOps, and Finance to support forecasting, territory planning, account prioritization, sales performance, and revenue attribution.
• Create visibility into how enterprise customers adopt and use Higgsfield’s products to inform conversion, engagement, and expansion opportunities.
• Implement automated validation, monitoring, documentation, and governance to maintain data accuracy and consistency across systems.
• Find ways to improve pipeline performance, automation, and infrastructure as the business scales.

Skills

Data pipelines design

SQL

Python

Data modeling

Data architecture

Data quality

B2B SaaS metrics

Stakeholder communication

Tools

Snowflake

BigQuery

Redshift

dbt

Airflow

Dagster

Salesforce

HubSpot

Stripe

Job description

Higgsfield AI is hiring a Data Engineer for hybrid work in the San Francisco Bay Area to build and scale data infrastructure for B2B and go-to-market operations.

Responsibilities

• Design, develop, and maintain scalable data pipelines that integrate CRM, billing, product analytics, and other business-critical systems.
• Connect product usage, account activity, sales pipeline, contracts, and revenue data to deliver a consistent view of B2B customers.
• Build data models that are reliable and well-documented for pipeline analytics, revenue reporting, customer segmentation, and retention and expansion insights.
• Collaborate with Sales, RevOps, and Finance to support forecasting, territory planning, account prioritization, sales performance, and revenue attribution.
• Create visibility into how enterprise customers adopt and use Higgsfield’s products to inform conversion, engagement, and expansion opportunities.
• Implement automated validation, monitoring, documentation, and governance to maintain data accuracy and consistency across systems.
• Find ways to improve pipeline performance, automation, and infrastructure as the business scales.

Requirements

• 6-8+ years of experience in Data Engineering, Analytics Engineering, or a closely related technical role.
• Strong proficiency in SQL and Python, including experience building production-grade ETL/ELT pipelines.
• Experience with modern data warehouses, including 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 including 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 needs into scalable technical solutions.
• Strong communication skills, including experience partnering directly with nontechnical stakeholders.

Technical Skills

• SQL, Python
• ETL/ELT
• Snowflake, BigQuery, Redshift
• dbt, Airflow, Dagster
• Salesforce, HubSpot, Stripe

Compensation & Benefits

• Base Salary: Anticipated range $200,000 - $260,000 per year, depending on experience, skills, scope, and location.
• Bonus: Bonus eligible; may participate in the Company’s discretionary annual bonus program.
• Equity: Eligible to participate in the company’s stock option program and share in long-term growth.
• Medical, dental, and vision insurance.
• Competitive 401(k) retirement plan with company matching.
• Comprehensive benefits package designed to support employees professionally and personally.
• Opportunity to work on ambitious AI products with a highly experienced, fast-moving, and international team.
• Significant ownership, direct impact, and opportunities for professional growth as the company scales.

Hybrid Role (San Francisco Bay Area)

• Expected to work from the San Francisco office three full days per week, with remaining days remote.
• Expected to be available during agreed working hours and maintain sufficient overlap with the relevant team’s time zone.
• In-person collaboration, active communication, responsiveness, and close partnership across teams are valued.

Location: San Francisco, CA (hybrid)

Experience: Minimum 6 years

Salary: USD 200,000 - 260,000 per year