Senior Backend Software Engineer – Node.js & Data
Role Overview
Senior, hands-on backend engineering role focused on Node.js and data-intensive applications.
The posting states work type as on-site or remote, without specifying which arrangement applies to a candidate.
Key Skills for This Role
Full Job Posting
Role overview
Senior, hands-on backend engineering role focused on Node.js and data-intensive applications.
The posting states work type as on-site or remote, without specifying which arrangement applies to a candidate.
Responsibilities
- Design scalable Node.js and TypeScript backend systems and high-performance REST APIs.
- Work with large datasets; design, optimize, and maintain MongoDB databases.
- Build data ingestion, transformation, matching, normalization, and other processing workflows.
- Integrate third-party APIs and external data sources; identify and resolve duplicate, inconsistent, or incomplete data.
- Improve API, database, and application performance; build background jobs, queues, caching, and asynchronous processing.
- Integrate AI and LLM services, troubleshoot production and data issues, and contribute to architecture decisions.
- Review code, maintain engineering standards, and collaborate with Product, Mobile, Web, Data, and AI teams.
Required experience
- 5+ years of backend software engineering experience; this is explicitly not a junior or entry-level position.
- Strong professional experience with Node.js and TypeScript; strong experience with NestJS and/or ExpressJS.
- Strong experience with MongoDB and Mongoose; experience with large or complex datasets, data modeling, and database optimization.
- Experience building and optimizing REST APIs and integrating third-party APIs and external data sources.
- Experience with Redis and background job processing, BullMQ and/or RabbitMQ, Docker, Git, and CI/CD.
- Understanding of scalable backend architecture and microservices, plus debugging and performance optimization skills.
- Data engineering experience in at least some areas including ingestion, transformation, matching, deduplication, data quality, ETL, or scheduled processing.
Additional skills
- AI and LLM integration experience is a strong advantage; examples include AI APIs, function calling, structured outputs, RAG, embeddings, vector search, and prompt engineering.
- Nice to have: web scraping, data extraction, Playwright or Puppeteer, proxy and anti-blocking solutions, AWS, MongoDB Atlas, WebSockets, Elasticsearch, or related platform experience.
- The employer seeks independent problem-solving, ownership through production deployment, architectural judgment, and clear communication with technical and non-technical teams.
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