Data Engineer, Finance

Superhuman is hiring a Data Engineer, Finance to build and own scalable data pipelines, datasets, and models used for revenue reporting within the Finance & Revenue team. You will work across Finance, Revenue Operations, Analytics, and Engineering to convert billing, bookings, customer, and product-usage signals into trusted metrics such as ARR and NRR.

Role Responsibilities

• Design, build, and own scalable data pipelines using Spark/Databricks to ingest and model billing, subscription, payment, and bookings data across the Superhuman Suite.
• Build and maintain foundational datasets for ARR, NRR, bookings, and other revenue metrics to ensure a consistent and trusted view of financial performance.
• Support revenue attribution by building and maintaining underlying datasets that connect product usage, customer lifecycle, and commercial signals into an explainable business performance view.
• Model revenue data into clean, well-documented, reusable tables that Finance, Revenue Operations, analysts, and business partners can self-serve.
• Own data quality, freshness, and reliability for revenue-critical datasets, including automated checks, monitoring, alerting, and reconciliation processes.
• Partner with Finance, Revenue Operations, Analytics Engineering, Product, and Engineering to translate business questions into robust data models and trustworthy metrics.
• Continuously improve the performance, cost efficiency, and developer experience of the finance and revenue data platform.

Required Qualifications

• 3+ years of experience building and operating production data pipelines and data platforms, ideally supporting finance, revenue, billing, or other business-critical analytical use cases.
• Advanced SQL skills and strong data engineering foundations, with hands-on experience in Spark and a modern lakehouse or cloud data warehouse such as Databricks, Delta Lake, dbt, Snowflake, or similar.
• Strong data modeling and data warehouse design capability, with experience transforming complex business processes and source-system data into reliable, reusable datasets.
• A rigorous approach to data quality, precision, observability, and reconciliation, particularly for datasets used in revenue reporting and business decisions.
• Experience with workflow orchestration and CI/CD for data, for example Databricks Workflows or Airflow with Git-based deployment.
• Comfort using AI-assisted development tools such as Codex or Claude Code, along with the judgment to validate and supervise outputs.
• Clear communication and effective collaboration with business partners, analysts, engineers, and leadership across technical and business audiences.
• Strong interest in business impact and the ability to turn ambiguous finance and revenue questions into scalable data products and trustworthy metrics.
• Self-directed problem-solving, including first-principles thinking, priority management across multiple projects, and effectiveness in a fast-paced, results-driven environment.

Technologies

• SQL
• Spark
• Databricks
• Delta Lake
• dbt
• Snowflake
• Databricks Workflows
• Airflow
• Git
• Codex
• Claude Code

Preferred Qualifications

• Direct experience supporting Finance, Revenue Operations, or revenue analytics, including metrics such as ARR, NRR, bookings, billing, or revenue attribution.
• Experience ingesting or modeling data from Stripe or similar billing, payments, ERP, or subscription-management systems.
• Experience with product-usage data, usage-based billing, or attribution models.
• A track record of building well-documented, self-serve data products relied upon by business and analytics teams.

Compensation and Benefits

Superhuman uses a market-based approach to compensation, and base pay may vary by location. US locations are categorized into two compensation zones based on proximity to hub locations. Expected salary ranges for this position are:

• US Zone 1: 175,000 to 245,000
• US Zone 2: 157,000 to 220,500

• Excellent health care (including medical, dental, vision, mental health, and fertility benefits)
• Disability and life insurance options
• 401(k) matching
• Paid parental leave
• 20 days of paid time off per year, 12 days of paid holidays per year, two floating holidays per year, and flexible sick time
• Generous stipends (including caregiving, pet care, wellness, home office, and more)
• Annual professional development budget and opportunities

Location, Employment Type, and Department

• Location: San Francisco, CA (hybrid). Hub locations include San Francisco and Seattle.
• Employment type: Full time
• Work model: Hybrid
• Department: Engineering, Product, Design, and Marketing; Engineering (Data / Data & Analytics)