Data Operations

Data Operations Finance Jobs

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Today

Data Engineer, Finance

Superhuman San Francisco, CA

San Francisco, CA

Today

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

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Job Description

Superhuman is seeking a Data Engineer, Finance to help build and operate scalable data pipelines, datasets, and models used for revenue reporting. In the Finance & Revenue organization, this role partners across Finance, Revenue Operations, Analytics, and Engineering to turn billing, bookings, customer, and product usage signals into trusted metrics such as ARR and NRR.

This hybrid position is based in the San Francisco, CA hub (with another hub listed in the process) and focuses on creating decision-grade, self-serve data foundations that revenue teams can rely on. The role also contributes to revenue attribution by linking product activity and lifecycle signals to commercial performance in an explainable way.

What you’ll do

Design, build, and take ownership of 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 provide a consistent view of financial performance.
Support the revenue attribution model by building and maintaining underlying datasets that connect product usage, customer lifecycle, and commercial signals.
Create clean, well-documented, reusable revenue tables so Finance, Revenue Operations, analysts, and business stakeholders can self-serve metrics.
Own data quality, freshness, and reliability for revenue-critical datasets, including automated checks, monitoring, alerting, and reconciliation.
Collaborate with Finance, Revenue Operations, Analytics Engineering, Product, and Engineering to translate business questions into robust models and trustworthy metrics.
Continuously improve the performance, cost efficiency, and developer experience of the finance and revenue data platform.

Required qualifications

3+ years building and operating production data pipelines and data platforms, ideally for finance, revenue, billing, or other business-critical analytical use cases.
Strong SQL skills and hands-on experience with Spark plus a modern lakehouse or cloud data warehouse such as Databricks, Delta Lake, dbt, Snowflake, or similar technologies.
Solid data modeling and warehouse design skills, with the ability to turn complex business processes and source-system data into clear, reliable, reusable datasets.
A rigorous approach to data quality, precision, observability, and reconciliation 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 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 in turning ambiguous finance and revenue questions into scalable data products and trusted metrics.
Self-starting problem-solving, ability to prioritize across multiple projects, and comfort working in a fast-paced, results-driven environment.

Technologies

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

Benefits

Excellent health care (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 those for caregiving, pet care, wellness, and your home office
Annual professional development budget and opportunities

Nice to have

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 relied on by business and analytics teams.

Compensation and location details

Superhuman uses a market-based approach to compensation, with base pay varying by location. The expected salary range for this role is USD 157,000 to 220,500 per year. In the US, two compensation zones are listed: US Zone 1: 175,000 to 245,000 and US Zone 2: 157,000 to 220,500.

This role is full-time and hybrid, with hubs listed as San Francisco and Seattle.

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1mo ago

Data Scientist, Finance

Ramp Financial New York, NY

New York, NY

1mo ago Closed

$137k - $297k/yr Full time 3d Design Tools Analytics Artificial Intelligence

This position is no longer accepting applications (closed Sep 11, 2026).

Job Description

Ramp Financial is building finance with modern data and practical innovation. In this hybrid role in New York, NY (HQ) with also San Francisco, CA, you will help develop models and production-ready data systems that surface financial insights for Finance teams and the broader business.

You will be part of the Data department and collaborate across Finance and data engineering to turn raw data into actionable reporting and decision support. Ramp also supports sustainable work through benefits designed for health, flexibility, and family life, including Flexible PTO, weekly coffee stipend, and comprehensive medical coverage for you.

What you’ll do

Build full stack data solutions: develop models that consume, transform, and expose data to stakeholders and production systems
Help drive a culture of experimental design, testing, and repeatable best practices
Influence processes, tools, and systems across the data team to enable scalable, better decisions
Partner with Finance teams such as GTM Finance and StratFin to develop financial insights that shape business decisions
Work closely with data engineering teams to capture, move, store, and transform raw data into highly actionable insights, and then work with business teams to turn insights into action

What you bring

Minimum 3 years of industry experience in Data Science, Software Engineering, or Finance
Strong AI proficiency and the ability to quickly adopt new skills and subject matter
A track record of shipping high quality products and features at scale
Comfort thriving in a fast-paced, constantly improving startup environment with iterative technical solutions
Familiarity with financial metrics and processes such as contribution profit, financial statements, and monthly close
Strong knowledge of SQL, preferably with Redshift, Snowflake, or BigQuery, including writing efficient SQL queries

Tools you may use

AI, SQL, Redshift, Snowflake, BigQuery, Fivetran, dbt, Looker, Hightouch, Omni, Sigma, Hex

Compensation

USD 137,120 - 297,330 per year (target base salary for SF/NY), with equity offers. Final compensation depends on location and level at hire.

Benefits and support

Flexible PTO
Centralized home-office equipment ordering
Health and wellness stipend
Budget for intra-office travel
Weekly coffee stipend
100% medical, dental & vision coverage for you, with partial coverage for dependents
One Medical annual membership
401(k) with employer match on contributions made while employed at Ramp
Fertility HRA (up to $10,000 per year)
Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay
Pet insurance
In-office perks: lunch, snacks, drinks, and more
Relocation support to NYC or SF (as needed)

United States benefits also include group coverage through Sun Life, Life, AD&D, and disability coverage, Fertility drug coverage (up to $4,000 lifetime), and a Group Retirement Plan (RRSP + DPSP), plus an Employee Assistance Program and virtual care through Lumino Health, and private medical insurance options including Freedom Elite, virtual GP and at-home care via eMed x Livi, and workplace pension support through Penfold with a salary sacrifice option.

Employment type: Full time | Location type: Hybrid | Department: Data

Other notes: Ramp will consider for employment qualified applicants with arrest and conviction records in line with the San Francisco Fair Chance Ordinance. Ramp warns that it will only contact candidates through official @Ramp.com email addresses and will never request payment or sensitive personal information during hiring.

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