Maintain and enhance a Django service while designing APIs focused on performance and scalability, collaborating with DevOps to ensure reliability in production environments.
Ajax Systems is a full-cycle company working from idea generation and R&D to mass production and sales. We do everything: we produce physical devices (the system includes many different sensors and hubs), write firmware for them, develop the server part and release mobile applications. The whole team is in one office in Kyiv, all technical and product decisions are made locally.
We’re looking for a Data Engineer to join us and continue the evolution of a product that we love: someone who takes pride in their work to ensure that user experience and development quality are superb.
Required skills:
- 4+ years of experience with Python in commercial projects
- Hands-on experience with Django, including working with the ORM and migrations
- Basic to intermediate experience with FastAPI or readiness to learn and apply it in practice
- Solid understanding of relational databases and SQL fundamentals
- Familiarity with REST API concepts and HTTP basics
Nice to have:
- Experience writing and optimizing non-trivial SQL queries
- Experience in working with large volumes of data and databases.
- Experience with monitoring and logging tools (ElasticSearch, Kibana).
- Experience with Docker and CI/CD pipelines.
- Understanding of cloud data platforms (AWS/GCP/Azure).
Tasks and responsibilities:
- Maintain, extend, and refactor an existing Django service
- Design, implement, and support APIs with a focus on performance, scalability, and reliability (FastAPI)
- Analyze, optimize, and refactor complex database queries to achieve maximum performance and efficient resource usage
- Work closely with relational databases (primarily MySQL, and a little bit of PostgreSQL) to improve query execution plans, indexing strategies, and data modeling
- Identify performance bottlenecks across the application stack (database, ORM, application logic)
- Collaborate with DevOps and infrastructure teams to ensure efficient data access patterns and stable production environments
- Coverage of new features through tests, as well as additions to existing ones
- React to monitoring alerts and ensure the stability and reliability of pipelines
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