Manager, Data Engineering

Want to help us, help others? We’re hiring!

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 are seeking a Manager, Data Platform to lead the team that builds and operates the foundation every other data team depends on. This role is accountable for the infrastructure, capabilities, and tooling that make our data platform observable, reliable, cost-efficient, and ready to scale with current and future traffic. You will translate platform strategy into a clear roadmap, establish owners and deadlines, and deliver measurable improvements in reliability, visibility, and efficiency. You will partner closely with Data, ML/AI, and Product Engineers, Data Scientists, Security, and Privacy teams to manage risks and dependencies and make clear trade-off decisions. You will also hire, coach, and develop engineers while partnering with Staff+ engineers and architects on technical direction. Success will be measured by platform reliability and scalability, cost transparency and efficiency, team health, and the productivity of the teams who build on the platform.

Candidates considered for this role will be located in Buenos Aires, Argentina. There will be an in-office requirement of 3x a week.

The Job

• Own the Platform Roadmap & Outcomes: Partner with data product management to build the team's roadmap and backlog, tying platform investments to measurable outcomes such as reliability, scalability, cost savings, and developer productivity.

• Build Observability into the Platform: Lead the design and delivery of monitoring, alerting, and observability capabilities, including pipeline health, data freshness and quality signals, distributed tracing, SLOs/SLAs, and incident detection, so issues are found before our stakeholders find them.

• Deliver Cost Visibility & Optimization: Build the tooling and practices that give teams clear attribution of compute, storage, and pipeline spend. Drive FinOps habits such as budgets, anomaly detection, and efficiency targets without sacrificing reliability.

• Scale for Current & Future Demand: Own capacity planning, performance engineering, and architecture evolution so batch and streaming systems handle growth, seasonal spikes, and viral fundraising moments.

• Build Self-Service Tooling & Paved Roads: Create reusable frameworks, CI/CD, infrastructure-as-code, orchestration standards, and templates that let data teams ship quickly, safely, and consistently.

• Drive Reliability & Operational Excellence: Establish on-call practices, incident response, postmortems, runbooks, and sustainable support models. Use operational metrics to continuously improve.

• Partner Cross-Functionally: Build strong relationships with Data, ML/AI, and Product Engineers, Data Scientists, Security, and Privacy teams to understand platform needs and communicate priorities, trade-offs, and outcomes clearly.

• Drive Delivery & Accountability: Set clear owners, milestones, and deadlines; hold the team accountable for commitments; and communicate progress and decisions transparently.

• Lead, Grow & Manage Performance: Hire, coach, and develop a high-performing team through regular feedback, 1:1s, performance management, and meaningful career development.

• Manage Risks & Dependencies: Proactively identify and resolve delivery risks, cross-team dependencies, migration challenges, and blockers before they affect outcomes.

• Make Prioritization & Trade-Off Decisions: Balance new capabilities against reliability, security, cost, technical debt, and team capacity, and explain the rationale clearly.

• Partner on Technical Direction: Work with Staff+ engineers and architects to align architecture and tooling decisions with business priorities and long-term platform strategy.

• Improve Team Efficiency with AI: Champion responsible use of AI tools and agents in platform operations (anomaly detection, incident triage, cost analysis), development, and documentation.

You

• Have excellent communication and leadership skills, with the ability to build trust, align diverse stakeholders, navigate conflict, and communicate priorities, trade-offs, and outcomes clearly.

• Bring 5+ years of experience in data engineering, platform engineering, SRE, or related fields, including at least 2+ years directly managing engineers or platform teams.

• Have a track record of driving predictable delivery, establishing clear ownership and deadlines, and holding teams accountable for commitments.

• Have proven success hiring, coaching, developing, and retaining high-performing engineering teams.

• Show strong judgment in prioritization, resource allocation, risk management, and making difficult trade-off decisions.

• Have deep hands-on experience building and operating data platforms at scale, including distributed systems, batch and streaming architectures, orchestration, and cloud infrastructure.

• Can guide design and delivery using Python, SQL, Spark, Kafka, Snowflake or BigQuery, Airflow, dbt, Kubernetes, Terraform (or similar IaC), and CI/CD, stepping in when needed to review designs, troubleshoot issues, and unblock the team.

• Have experience with observability and monitoring tooling and practices (e.g., Monte Carlo, Prometheus/Grafana, OpenTelemetry, other data observability tools), including defining SLIs/SLOs and running incident management.

• Have working knowledge of data lineage and cataloging (e.g., OpenLineage, DataHub, Atlan, or similar) and of data governance, privacy, security, and compliance.

• Have experience with cloud cost management and FinOps practices, including cost attribution, forecasting, and optimization.

Why you’ll love it here

• Make an Impact : Be part of a mission-driven organization…