E-Solutions
Backend Developer / Data Engineer
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Warsaw, Poland
Work mode:
Onsite
Published on:
15 September 2026
What they need
Role Backend Developer / Data Engineer
Location Warsaw, Poland – Hybrid
Type Full-Time
Job Description
Role: Backend Developer / Data Engineer
Experience level: At least 8 years of professional experience.
Key technical requirements
· Python Proficiency: Strong proficiency in Python, including writing clean, type-hinted, scalable, and testable code. Strong focus on code quality, maintainability, and engineering best practices.
· Backend And Data Pipelines Development: Proficiency to develop REST applications with FastAPI. Experience with databases (e.g. PostgreSQL). Experience with designing and implementing ETL pipelines.
· Development Practices: Strong knowledge of Git version control. Experience with GitHub Actions and building CI/CD pipelines.
· Cloud / Platform Requirements: Strong knowledge of Docker and application containerization. Good understanding of core AWS services, particularly AWS Glue, AWS Batch, ECS, S3, and ECR.
Nice-to-have requirements
· Observability: Basic knowledge of OpenTelemetry, including metrics, distributed tracing, logging, and observability best practices.
· Platform & Security: Basic knowledge of Kubernetes and Helm Charts. Familiarity with OAuth 2.0 and modern authorization mechanisms.
· Data & Architecture: Understanding of relational databases and data engineering best practices. Experience building cloud-native and microservices-based systems.
· AI / Machine Learning: Interest in or experience working with AI/ML systems and LLM-based applications.
Language requirements (language, proficiency level)
· English: C1 proficiency level.
Description of the project in which the service will be provided
One of the projects is a RAG-based consumer assistant, the second one is focused on in-depth various types of document analysis and a chat-based interface. Both projects need further development and maintenance.
Technologies utilized
Python, AWS, Kubernetes, LLMs, Classical AI/ML.
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