Data Engineer, Strategic Finance

Whop; Palo Alto (CA); On-site; USD 200,000 - 300,000; Full time

Benefits offered by this job

Competitive base salary

Meaningful equity

Full benefits

Job summary

Whop is seeking a Data Engineer to enhance decision-making through data insights. This role involves building datasets and pipelines that directly impact financial product features.

The ideal candidate will bring over 3 years of experience in Data Engineering, with strong skills in SQL and Python. A competitive salary ranging from $200,000 to $300,000 is offered, plus equity and full benefits.

Qualifications

• 3+ years in Data Engineering, Analytics Engineering, or a closely related role.
• Deep expertise in SQL and Python.
• Proven experience defining financial and operating metrics.

Responsibilities

• Find insights that change business decisions.
• Write production code and build features on Whop Financial Reports.
• Ingest payment-processor settlement data accurately.

Skills

SQL

Python

Data modeling

Version control (GitHub)

Financial metrics knowledge

Education

3+ years in Data Engineering or related roles

Tools

dbt

BigQuery

Snowflake

Job description

About Whop

Whop is a financial technology company on a mission to provide the world with sustainable income. Our vision is to create the world's 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, whop.com.

About the Role

We're 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 isn't 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. You'll write production code and ship changes directly to Whop's financial products. You'll 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 "here's what we should do," this role is unusually high‑leverage.

What You'll Do

• 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 it's 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.

What You'll Bring

• 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.

Compensation & Benefits

Competitive base salary, meaningful equity, and full benefits. Target base range: $200,000-$300,000, depending on level and experience. This role can flex to a Senior level for the right candidate.