Data Engineer, Finance

Superhuman

. Design, build, and own scalable Spark/Databricks data pipelines ingesting and modeling billing, subscription, payment, and bookings data across the Superhuman Suite .

Posted 9/24/2026full-timeUnited StatesMid-LevelSenior💰 $175,000 - $245,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining scalable data pipelines using Spark and Databricks, with a strong focus on data quality and revenue metrics. Proficient in SQL and data modeling, capable of translating complex business processes into reliable datasets for finance and revenue operations.

Highest-signal resume keywords

SQL ProficiencySpark Data Pipeline DevelopmentData Modeling and Warehouse DesignData Quality and ObservabilityWorkflow Orchestration with CI/CD

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLSparkData ModelingData Warehouse DesignData QualityObservabilityReconciliationWorkflow OrchestrationCI/CDData Transformation

Soft Skills

Clear CommunicationEffective CollaborationPriority Management

Tools & Technologies

DatabricksDelta LakeDbtSnowflakeDatabricks WorkflowsAirflowAI-Assisted Development Tools

Industry Keywords

FinanceRevenue OperationsBillingSubscription ManagementAttribution ModelsProduct Usage Data

Tech Stack

Tools & technologies

AirflowCloudERPSparkSQL

About the role

Key responsibilities & impact

Design, build, and own scalable Spark/Databricks data pipelines ingesting and modeling billing, subscription, payment, and bookings data across the Superhuman Suite
Build and maintain foundational datasets for ARR, NRR, bookings, and other revenue metrics
Contribute to the revenue attribution model by maintaining datasets connecting product usage, customer lifecycle, and commercial signals
Model revenue data into clean, documented, reusable tables for Finance, Revenue Operations, analysts, and business partners
Own data quality, freshness, and reliability for revenue-critical datasets through automated checks, monitoring, alerting, and reconciliation
Partner with Finance, Revenue Operations, Analytics Engineering, Product, and Engineering to translate business questions into robust data models and trustworthy metrics
Improve performance, cost efficiency, and developer experience of the finance and revenue data platform
Own revenue-critical systems end-to-end and influence the platform roadmap

Requirements

What you’ll need

3+ years of experience building and operating production data pipelines and data platforms
Experience ideally supporting finance, revenue, billing, or other business-critical analytical use cases
High proficiency in SQL
Strong data engineering foundations
Hands-on experience with 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 skills
Experience transforming complex business processes and source-system data into reliable, reusable datasets
Experience with data quality, precision, observability, and reconciliation
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 such as Codex or Claude Code
Ability to validate and supervise AI-assisted development output
Clear communication and effective collaboration with business partners, analysts, engineers, and leadership
Ability to translate between technical and business audiences
Ability to manage priorities across multiple projects in a fast-paced, results-driven environment
Direct Finance, Revenue Operations, or revenue analytics experience is nice to have
Experience with Stripe or similar billing, payments, ERP, or subscription-management systems is nice to have
Experience with product-usage data, usage-based billing, or attribution models is nice to have
Track record of building well-documented, self-serve data products is nice to have

Benefits

Comp & perks

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
Flexible sick time
Caregiving stipend
Pet care stipend
Wellness stipend
Home office stipend
Annual professional development budget
Professional development opportunities
Flexible hybrid working model