Staff Data Engineer (Accounting)

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GoFundMe is the world’s most powerful community for good, dedicated to helping people help each other. By uniting individuals and nonprofits in one place, GoFundMe makes it easy and safe for people to ask for help and support causes—for themselves and each other. Together, our community has raised more than $40 billion since 2010.

We’re looking for a Staff Data Engineer, Accounting to build the scalable data infrastructure, automation, and compliance-ready platform capabilities that support Accounting and Finance at GoFundMe.

You will work at the intersection of data engineering, accounting automation, financial reporting, and compliance-driven platform requirements. You will partner closely with the Analytics team to build the engineering foundation beneath their analytical and reporting work. You will also collaborate with Accounting and Finance leadership, Payments and Engineering to ensure that financial data is complete, accurate, traceable, and ready to support increasingly complex regulatory and operational requirements. Accounting will define business priorities and requirements. You will own how those requirements are translated into scalable pipelines, data models, controls, monitoring, and platform capabilities.

If you are energized by building reliable financial data systems, automating complex operational processes, and designing infrastructure that can withstand regulatory and audit scrutiny, this role is for you.

Candidates considered for this role will be located in Buenos Aires.

The Job

Build the data engineering foundation for Accounting: Own the pipelines, transformations, and technical systems that power Accounting and Finance reporting. Ensure financial data is complete, timely, accurate, and traceable from source systems through downstream reporting and reconciliation workflows.

Partner with Analytics for Accounting: Work closely with the Analytics team to build the engineering foundation beneath financial reporting, automation, and analysis. Translate analytical and business requirements into durable data products while enabling the analyst to own the reporting, insight, and business-facing layers.

Use AI to increase engineering impact: Integrate AI-assisted tools and coding agents into your day-to-day workflow to deliver more than would be possible through traditional development practices alone. Use them to accelerate prototyping, implementation, test generation, debugging, data investigation, documentation, and repetitive engineering work without compromising accuracy, maintainability, security, or review standards.

Enable compliance-driven platform requirements: Build the data capabilities required to support regulatory and compliance reporting, as GoFundMe operates and scales in regulated financial services environments. Design compliance reporting infrastructure to be automated, repeatable, and audit-ready from inception, leveraging AI-assisted tooling and scalable pipelines so that regulatory obligations are met through durable systems rather than manual processes. Partner with Accounting, Tax, Compliance, Payments, Legal, and Engineering to translate regulatory requirements into reliable, repeatable, and auditable data processes.

Support financial reporting and audit readiness: Develop data infrastructure that makes financial reporting reproducible, traceable, and defensible. Ensure pipelines and transformations retain appropriate lineage, documentation, controls, and evidence to support internal reviews, external audits, and enterprise-scale reporting requirements.

Strengthen transaction-level reconciliation: Build and maintain systems that support reconciliation across payment processors, internal transaction systems, the ledger, and financial platforms such as NetSuite. Develop controls and monitoring that surface missing, duplicated, delayed, or inconsistent transactions before they affect reporting or compliance obligations.

Own data integrity across financial systems: Monitor the completeness and accuracy of data moving between source systems, payment platforms, the internal transaction ledger, the data warehouse (Snowflake), and NetSuite. Use automation and AI-assisted investigation where appropriate to identify patterns and accelerate root-cause analysis, while independently validating conclusions and implementing durable fixes rather than relying on recurring manual corrections.

Establish engineering standards for financial data: Define best practices for how financial data pipelines and models are designed, tested, documented, monitored, and maintained. Build systems that are resilient, observable, and understandable by teams beyond their original authors.

Improve data reliability and observability: Implement automated testing, alerting, lineage, and monitoring for critical financial datasets. Use modern tooling to expand test coverage, identify anomalies, and shorten the time required to detect, investigate, and resolve data quality issues.

Manage stakeholders across functions: Operate independently across Accounting, Finance, Tax, Payments, Compliance, Analytics, and Engineering. Translate complex business and regulatory requirements into clear technical plans, communicate tradeoffs, and build alignment across technical and non-technical stakeholders.

You

Experience & Education

8+ years of experience in data engineering, software engineering or a related technical field

Experience designing and operating production-grade data pipelines and platforms, ideally in finance, fintech, banking, or payments

Experience working with transaction-level financial data, reconciliation processes, or financial systems in audit-driven or regulated environments

Demonstrated ability to own complex technical domains end to end with minimal direction

Experience supporting enterprise scaling, SOX readiness, external audits, IPO preparation, or regulatory reporting is a strong plus

Core Skills

Strong knowledge of modern data architecture, including ingestion, transformation, orchestration, modeling, testing, and observability

Ability to translate ambiguous Accounting, Finance, and Compliance requirements into scalable technical solutions

Strong systems thinking, with a focus on automation, durable controls, and preventing recurring issues

Sound judgment around data quality, reliability, risk, and the tradeoffs between immediate needs and long-term platform design

Ability to work effectively with technical and non-technical stakeholders and communicate clearly with senior leaders

A rigorous approach to validating outputs, investigating discrepancies, and resolving root causes

Technical Skills

Advanced SQL and strong experience with Snowflake, dbt, and large-scale data modeling

Strong proficiency in Python or another language used to build production pipelines and automation

Experience with orchestration tools, APIs, event-based and batch processing, and third-party integrations

Experience implementing automated testing, data quality controls, lineage, monitoring, and alerting

Strong software engineering practices, including version control, code review, CI/CD, testing, and documentation

Advanced fluency with AI assistants, coding agents, and agentic workflows, with a demonstrated ability to use them to materially increase the speed, quality, and scope of delivery

Familiarity with BI tools such as Looker and financial or payment systems such as NetSuite, Stripe, or Adyen is a plus

Leadership & Collaboration

Operates independently, takes accountability for outcomes, and sets technical direction across teams

Partners effectively with Analytics, Accounting, Tax, Finance, Payments, Compliance, and Engineering

Communicates technical concepts, risks, dependencies, and tradeoffs clearly to technical and non-technical audiences

Builds maintainable, documented solutions and helps othe