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The selected candidate will join the software development team responsible for a proprietary data analytics and modeling platform. As a Junior Backend Software Engineer (Python), the candidate will contribute to the design, development, and maintenance of backend services, working under the guidance of experienced engineers and within structured development processes. The position is open to candidates close to graduation as well as to professionals with up to a few years of experience, interested in growing within a structured software development environment.
Job Responsibility:
Contribute to the development and maintenance of backend services and APIs
Implement software components in accordance with defined architectural and coding standards
Collaborate with team members to analyze requirements and support their technical implementation
Apply secure coding practices and follow internal guidelines to ensure system security, reliability, and robustness
Participate in code reviews and technical discussions to support continuous learning
Support testing, debugging, and system improvement activities
Requirements:
Degree in Computer Science, Software Engineering, or a related field (or close to completion)
Solid foundations in software engineering principles and programming concepts
Basic understanding of backend architectures and web-based applications
Familiarity with Git for version control, including the use of GitHub
Motivation to learn, attention to quality, and ability to work effectively in a team environment
Good written and spoken English in a professional and technical context
Nice to have:
Python for backend development
Pandas and NumPy for data manipulation
Apache Spark for distributed data processing
Distributed architectures and microservices, including synchronous and asynchronous communication, REST and/or GraphQL APIs, and message-based systems such as RabbitMQ
MongoDB as the primary database technology, with exposure to relational and other NoSQL databases
Test-Driven Development (TDD), unit testing, and Continuous Integration practices
Containerization and orchestration tools such as Docker and Kubernetes
Cloud platforms (AWS, Azure, or GCP)
Use of generative code tools based on Large Language Models (e.g., GitHub Copilot)
Agile development methodologies
What we offer:
Total Compensation (fixed and variable components)