Finance Data Developer Jobs

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1d ago

Data Engineer, Finance

Superhuman San Francisco, CA

San Francisco, CA

1d ago

$157k - $221k/yr Full time Apache Airflow Automation Big Data

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Job Description

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

Responsibilities

Design, build, and own scalable data pipelines using Spark and 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 the revenue attribution model by building and maintaining underlying datasets that connect product usage, customer lifecycle, and commercial signals into an explainable view of business performance.
Model revenue data into clean, documented, reusable tables that Finance, Revenue Operations, analysts, and business partners can self-serve from.
Own data quality, freshness, and reliability for revenue-critical datasets using 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 performance, cost efficiency, and developer experience for the finance and revenue data platform.

Requirements

3+ years of experience building and operating production data pipelines and data platforms, ideally for finance, revenue, billing, or other business-critical analytical use cases.
Strong proficiency in SQL and solid data engineering foundations, with hands-on experience in Spark and a modern lakehouse or cloud data warehouse (including Databricks, Delta Lake, dbt, Snowflake, or similar).
Strong data modeling and data warehouse design skills, including the ability to translate complex business processes and source-system data into clear, reliable, reusable datasets.
High standards for data quality, precision, observability, and reconciliation, especially for datasets used in revenue reporting and business decision-making.
Experience with workflow orchestration and CI/CD for data, such as Databricks Workflows or Airflow, with Git-based deployment.
Comfort using AI-assisted development tools like Codex or Claude Code, along with judgment to validate and supervise outputs.
Clear communication and collaboration across business partners, analysts, engineers, and leadership, including translating between technical and business audiences.
Strong interest in business impact, with the ability to turn ambiguous finance and revenue questions into reliable, scalable data products and metrics.
Self-starting problem-solving approach, ability to manage priorities across multiple projects, and comfort in a fast-paced, results-driven environment.

Technologies

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

Compensation and Benefits

Salary range (annual): USD 157,000 - 220,500 per year.

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

Superhuman takes a market-based approach to compensation, so base pay may vary by location. Expected ranges may be modified in the future.

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 (caregiving, pet care, wellness, home office, and more)
Annual professional development budget and opportunities

Nice to Have

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 working with product-usage data, usage-based billing, or attribution models
A track record of building well-documented, self-serve data products used by business and analytics teams

Location and Employment Details

Location: San Francisco, CA (hybrid)
Hub locations: San Francisco; Seattle
Employment type: Full time
Location type: Hybrid
Department: Engineering, Product, Design, and Marketing (Engineering - Data / Data/Analytics Engineer)

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