Data Engineer, Strategic Finance

Whop is a financial technology company on a mission to provide the world with sustainable income. Our vision is to create the worlds largest internet market where people can create connect and transact all from a single platform. Whop enables individuals and businesses to accept payments launch ventures and engage with others across the network. Today people on Whop earn $4 billion annually across 145 countries. For more information visit .

Were hiring our first dedicated Data Engineer inside Strategic Finance and the job is simple to state and hard to do well: make everyone at Whop smarter with the insights hidden in our data and change how the company makes decisions.

Whop generates an enormous amount of data every payment dispute refund and ad campaign tells us something about the business. Most of it isnt yet answering directly the questions we are actually asking. You will build the datasets models and metrics that turn that raw signal into fast trustworthy answers and then push those answers in front of the people making the calls so that a good decision is the path of least resistance.

This is a hands-on engineering role not a reporting seat. Youll write production code and ship changes directly to Whops financial products. Youll build and own the data pipelines that ingest payment-processor settlement data into that ledger encode accounting logic in code (bad-debt recognition FX gain/loss revenue categorization) and make the reported numbers reconcile to source.

If you combine engineering rigor with genuine curiosity about the business and a knack for turning numbers into heres what we should do this role is unusually high-leverage.

• Turn data into decisions. Find the insights that change what Whop does surface trends risks and opportunities in payments growth and unit economics and get them in front of the right people in a form they can act on immediately.
• Ship Whop financial product. Write production code and build features on Whop Financial Reports so its reliable enough to close the books on and useful to every merchant.
• Build and own the ingestion pipelines. Ingest and backfill payment-processor settlement data into the ledger at scale and across currencies and geographies so reported financials are complete and accurate always.
• Own the financial semantic layer. Define and standardize metric logic (GMV/GTV revenue take rate contribution margin COGS/GP per business LTV/CAC retention/cohorts chargeback and dispute rates) so one metric means one thing across the organization.
• Make finance and the business self-serve. Partner with leadership to ship intuitive trustworthy Metabase dashboards and data models so every stakeholder can answer their own questions with confidence and stop pinging you for a number.
• Set standards. Establish data modeling conventions testing documentation and access controls and own data quality and lineage across the stack.

• 3 years in Data Engineering Analytics Engineering or a closely related role ideally in a high-growth or fintech environment.
• Deep expertise in SQL and Python plus a modern transformation and warehouse stack (dbt BigQuery preferred; Snowflake/Redshift equivalent fine).
• Proven experience defining financial and operating metrics and resolving data inconsistencies across complex multi-system pipelines.
• Strong grounding in version control (GitHub) CI/CD testing and documentation as defaults not afterthoughts.
• Working knowledge of financial concepts: revenue margin LTV/CAC retention/churn and the difference between an accounting number and a product metric.
• Bias for action: you ship usable iterative data models that deliver value now over waiting on the perfect architecture.
• A strong communicator comfortable with ambiguity building trust across Finance Product GTM and Exec partners.

Competitive base salary meaningful equity and full benefits. Target base range: $200000-$300000 depending on level and experience. This role can flex to a Senior level for the right candidate.