Job Description
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Company Overview
A rapidly growing technology and financial platform is focused on helping individuals build sustainable income through digital commerce. The platform serves a large and growing user base, processing significant transaction volumes across payments, disputes, refunds, advertising, and other financial activities. The organization is continuing to expand its financial infrastructure and data capabilities to support informed decision-making at scale.
The organization is hiring its first dedicated Analytics Engineer within Strategic Finance. This role will focus on transforming complex business data into actionable insights that improve company-wide decision-making. The successful candidate will build datasets, analytical models, and standardized metrics that turn raw data into reliable answers for Finance, Product, Go-to-Market, and executive stakeholders.
The role will involve writing production code and contributing directly to financial products. The Analytics Engineer will build and maintain data pipelines that ingest payment-processor settlement information into financial ledgers, implement accounting logic through code, and ensure reported financial figures consistently reconcile with source systems.
This is an on-site position based in Palo Alto, California.
Key Responsibilities
- Turn complex business data into actionable insights by identifying trends, risks, and opportunities across payments, growth, and unit economics.
- Develop and ship production features for financial reporting products, ensuring they are reliable enough to support financial close processes and useful to merchants.
- Build, maintain, and scale ingestion pipelines for payment-processor settlement data across multiple currencies and geographic regions.
- Backfill and validate financial data within the ledger to ensure reported financial information remains complete and accurate.
- Own the financial semantic layer and establish standardized definitions for key metrics, including GMV/GTV, revenue, take rate, contribution margin, COGS/GP, LTV/CAC, retention, cohorts, chargebacks, and dispute rates.
- Partner with company leadership to develop intuitive and trustworthy Metabase dashboards and data models.
- Enable Finance and business stakeholders to independently access and analyze reliable data without relying on engineering for routine questions.
- Establish data modeling standards, testing practices, documentation requirements, and access controls.
- Maintain data quality and lineage across the organization’s data stack.
- Collaborate with Finance, Product, GTM, and executive stakeholders to ensure analytics solutions address critical business needs.
Required Qualifications
- 3+ years of experience in Data Engineering, Analytics Engineering, or a closely related field, preferably within a high-growth or fintech environment.
- Advanced expertise in SQL and Python.
- Experience with modern data transformation and warehouse technologies such as dbt and BigQuery; equivalent experience with Snowflake or Redshift is also valuable.
- Proven ability to define financial and operational metrics and resolve inconsistencies across complex, multi-system data pipelines.
- Strong understanding of version control, particularly GitHub, as well as CI/CD, automated testing, and technical documentation.
- Working knowledge of financial concepts, including revenue, margin, LTV/CAC, retention, churn, accounting figures, and product metrics.
- Strong analytical and problem-solving skills with the ability to work effectively in ambiguous environments.
- Excellent communication and collaboration skills with the ability to build trust across Finance, Product, GTM, and executive teams.
Disclaimer
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