python developer

The Motortrade platform provides pricing, vehicle, mapping, and recommendation data through internal applications and integrations with external market data.

• Design, develop, and maintain data ingestion and transformation pipelines using Airflow for internal vehicle and contract data and external market data;
• Contribute to the design and evolution of the platform’s canonical data model, ensuring data quality, consistency, and traceability;
• Develop and maintain Python-based services and REST APIs providing pricing, vehicle, mapping, and recommendation data to internal applications, including the Motortrade platform;
• Build and support integrations with upstream and downstream systems through REST APIs and event-driven architectures;
• Produce clean, well-tested, and well-documented code;
• Implement monitoring, data validation, and production support processes;
• Collaborate with business and technical stakeholders to translate pricing strategies and business requirements into scalable, maintainable software solutions;
• Contribute to the Angular frontend where pricing and recommendation features are presented to end users.

• 3–5 Years of professional experience developing Python applications focused on backend systems or data engineering;
• Strong Python programming skills, including Pandas and REST API frameworks such as FastAPI or Flask;
• Solid SQL knowledge and practical experience with relational databases, particularly PostgreSQL and/or Oracle;
• Experience designing, building, and orchestrating data pipelines, preferably with Apache Airflow;
• Familiarity with Git, code reviews, automated testing, and CI/CD workflows;
• Good understanding of API design and system integration principles;
• Strong communication skills in English and the ability to work effectively in an international environment;
• Nice to have: Full-stack development experience, particularly with Angular; knowledge of cloud-native data platforms and containerization technologies; experience with Kafka; familiarity with data quality, monitoring, or observability tools; basic understanding of machine learning workflows and collaboration with data science teams; previous exposure to the automotive, leasing, vehicle pricing, or remarketing industry.

• Hybrid work in Warsaw, Poland.