We are looking for a Backend Software Engineer with strong hands-on expertise in Node.js, PostgreSQL, RabbitMQ, and Redis to join our core data services engineering team. In this role, you will design, build, and scale distributed microservices, REST APIs, and event-driven data pipelines handling high-throughput transactional and analytical workloads.
Responsibilities:
- Microservices and API Architecture: Architect, build, and maintain scalable, low-latency microservices and RESTful APIs using Node.js, Express.js, and TypeScript.
- Database Design and Performance Tuning: Design relational database schemas in PostgreSQL; optimize complex SQL queries, composite indexing, and database connection pools under concurrent traffic.
- Event-Driven Architecture: Implement event-driven queues, asynchronous background processing, and worker nodes using RabbitMQ to ensure fault-tolerant data flows.
- In-Memory Caching and Distributed Locking: Implement high-performance caching strategies, rate limiting, and distributed locking logic using Redis.
- Containerization and CI/CD: Containerize microservices using Docker and maintain automated deployment pipelines across cloud infrastructure (AWS/GCP).
- System Ownership: Take full end-to-end ownership of backend services from technical design and code reviews to production deployment, monitoring, and debugging.
Requirements:
- Experience: 3 to 5 years of solid hands‑on experience in backend software development.
- Core Stack: Expert‑level proficiency in Node.js, Express.js, and JavaScript (ES6+) / TypeScript.
- Database Mastery: Strong hands‑on expertise in PostgreSQL (schema design, complex query writing, indexing, and performance tuning).
- Messaging and Queues: Proven experience in asynchronous processing and event‑driven architectures using RabbitMQ (or Kafka/BullMQ).
- Caching and Storage: Hands‑on experience with Redis for caching, rate limiting, and session management.
- DevOps and Infrastructure: Strong experience with Docker containerization and CI/CD workflows.
- Mindset: Strong logical reasoning, problem‑solving skills, and a high‑ownership startup mindset.
Nice-to-Have Skills (Bonus):
- Exposure to analytical data engines and semantic layers like Trino, Presto, ClickHouse, or Cube.js .
- Practical experience with Python for data workflows or automation.
- Experience handling high TPS loads, large-scale batch pipelines, or high-volume transactional systems.
- Experience using modern AI development tools (e. g., Cursor, Claude, and GitHub Copilot) to accelerate engineering workflows.