Backend Engineer

Role OverviewWe’re seeking a versatile Backend Engineer proficient in Python and TypeScript to design, build, and maintain robust APIs and data services. You’ll collaborate across teams to deliver high-quality, scalable back-end systems under rapid iteration cycles.

Key Responsibilities·        API Design & Development

o  Build and maintain RESTful and/or GraphQL endpoints using Python (e.g. FastAPI, Flask) and TypeScript (Node.js, NestJS, or similar).

o  Define clear, versioned OpenAPI/Swagger (or GraphQL) specifications.

·        Data Modeling & Database Management

o  Design and optimize relational schemas (PostgreSQL) and NoSQL stores as needed.

o  Implement migrations, indexing strategies, and performance tuning.

·        Integration Services

o  Develop connectors and adapters for external systems (e.g. object storage, message queues, third-party APIs).

o  Ensure data consistency, validation, and error handling.

·        Collaboration & Documentation

o  Partner with frontend, DevOps, and product teams to refine requirements and troubleshoot issues.

o  Produce and maintain clear technical documentation for APIs, data models, and deployment processes.

Must-Have Qualifications·        1+ years professional experience in backend development using:

o  Python (FastAPI, Flask, or Django REST Framework)

o  TypeScript (Node.js, NestJS, Express, or equivalent)

·        Strong SQL skills; experience with ORMs (SQLAlchemy, TypeORM, Prisma, etc.).

·        Expertise in designing secure, well-documented APIs (REST or GraphQL) with JWT/OAuth2 authentication.

·        Proven ability to ship features quickly in an agile, startup-like environment.

·        Solid testing mindset: comfortable writing and maintaining automated test suites.

Nice-to-Have·        Experience with caching (Redis, Memcached) and message brokers (RabbitMQ, Kafka).

·        Familiarity with cloud platforms (AWS, GCP, Azure) and infrastructure-as-code (Terraform).

·        Knowledge of event-driven architectures or serverless patterns.

·        Prior exposure to data pipelines (Airflow, Prefect) or real-time streaming.