TeamSnap is seeking an Engineering Manager to lead our Payments team within our fully distributed engineering organization. Our stack includes Node, TypeScript, Elixir, SQL, React, and cloud-based services. As an engineering team, we architect and build scalable systems using a service-oriented and event-driven architecture that serves millions of daily users and amateur sports organizations.
The Payments team owns business-critical systems that support registration, payment collection, financial workflows, payouts, partner integrations, subscriptions, and operational support. This role will be responsible for helping the team deliver high-quality software while also creating a healthy, accountable, and growth-oriented team environment.
Unlike a pure Engineering Manager role, this person will also contribute directly as a senior engineer in targeted ways. That may include helping design and implement backend services, improving observability, debugging complex production issues, pairing with teammates, reviewing critical code paths, or taking on scoped technical work that helps the team deliver safely and effectively.
What You'll Do:
Architect, build, and evolve backend APIs, services, event-driven workflows, queues, background jobs, data models, caching strategies, and integrations that support millions of users and thousands of sports organizations.
Own complex backend product and technical work from discovery through design, implementation, rollout, production support, and long term maintainability.
Lead ambiguous technical initiatives by breaking down problems, identifying risks, making practical tradeoffs, and helping teams move from uncertainty to clear execution.
Improve the reliability, scalability, performance, and operability of production systems through thoughtful architecture, strong testing practices, database optimization, caching, monitoring, alerting, and incident follow-up.
Debug complex production issues by reasoning across application code, databases, caches, queues, jobs, observability data, and the broader request lifecycle.
Partner with Product, Design, Engineering, Infrastructure, Platform, Data, Support, and other teams to turn roadmap needs into durable backend systems and practical delivery plans.
Strong interpersonal skills with the ability to give and receive constructive feedback, mentor engineers, influence cross-team alignment and articulate technical trade-offs to non-technical stakeholders
What Will Set You Up for Success:
Staff level backend engineering depth, with a strong track record building and operating high-scale APIs, services, distributed systems, or shared product capabilities in production.
Strong command of backend technologies such as Node, TypeScript, Elixir, Ruby/Rails, Java, Go, Python, or similar, including runtime behavior, failure modes, and production tradeoffs.
Strong SQL and relational database judgment, including indexing, query optimization, migrations, profiling, data modeling, transactions, read and write patterns, and performance tuning.
Practical understanding of service-oriented architecture, event-driven architecture, queues, background jobs, webhooks, Redis or similar caching tools, and systems that need to scale under real production load.
Working knowledge of production infrastructure and platform concerns, enough to reason through deployments, containers, CI/CD pipelines, cloud services, networking basics, observability, and operational debugging.
Strong production ownership mindset, with the ability to use logs, metrics, traces, dashboards, alerts, incident reviews, and system behavior to improve reliability over time.
Demonstrated ability to lead through influence, mentor engineers, facilitate technical decisions, communicate tradeoffs clearly, and connect backend technical choices to customer impact, business needs, and long term maintainability.
Bonus:
Previous work in or close partnership with infrastructure, platform, SRE, DevOps, or data teams.
Familiarity with Elasticsearch, BigQuery, analytics pipelines, search infrastructure, reporting workflows, or high-volume data processing.
Responsible use of AI-assisted engineering workflows to improve debugging, testing, documentation, refactoring, prototyping, or developer experience without compromising quality or understanding.
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