[Remote] Full-Stack (Python/Java & React/Typescript)
Note: The job is a remote job and is open to candidates in USA. Avenue Code is seeking a Full Stack Engineer to join their Analytics Platform product area, focusing on building the foundational infrastructure that supports data science work at Spotify. The role involves developing full-stack capabilities, designing features for data scientists and product builders, and contributing to the evolution of analytics tools for AI-era data science.
Responsibilities
- Build and maintain full-stack capabilities across Python/Java services and data pipeline integrations on the backend, to React/TypeScript interfaces on the frontend
- Design and ship features that meaningfully improve how data scientists, analysts, and product builders do their work across interactive querying, managed environments, insight creation, and data discovery
- Contribute to the evolution of our analytics stack for AI-era data science: supporting Claude Code integrations, MCP-based tooling, and agentic workflows
- Participate actively in technical design, architecture decisions, and code reviews
- Collaborate with data scientists, product managers, and partner teams to understand user needs deeply and translate them into high-quality technical solutions
- Help the team stay ahead of a fast-moving AI landscape: evaluate emerging tooling and patterns, and build things that age well as the ecosystem evolves
- Maintain and improve the reliability, scalability, and developer experience of the infrastructure thousands of Spotifiers depend on every day
Skills
- You have solid professional software engineering experience, with demonstrated depth in both backend and frontend development
- You're comfortable across the stack: backend services (Python or JVM strongly preferred), frontend React/TypeScript, and at least some experience with data infrastructure (BigQuery, Notebooks)
- You've built internal tools, developer platforms, or analytics surfaces before, and you understand what makes a good developer experience
- You have strong engineering fundamentals: you think carefully about APIs, data models, system design, and making the right tradeoffs between simplicity and capability
- You care about craft. You write code that's readable, tested, and maintainable — and you hold yourself and others to that standard
- You've developed solutions for AI-native teams. You're already using LLM-native tooling in your development workflow. You have opinions about how AI changes the way data teams should work, and you're excited to build for that future
- You're a strong communicator who can engage directly with technically sophisticated users, surface ambiguity early, and work collaboratively across functions
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