Cloud & Data Engineer (GCP)

Quick Facts

• Collaboration model: B2B contract
• Location: hybrid (Wrocław) or 100% remote

Description

Join the In-store Sensorics and Data area as a B2B contractor and help build data-driven solutions for dm stores—from sensor data collection to scalable cloud platforms and AI-supported services. You will develop reusable data products based on Data Mesh principles, implement backend services and REST/GraphQL interfaces, and automate deployments using Infrastructure-as-Code. The role emphasizes high-quality code and data and cross-functional collaboration.

Role & Responsibilities

• Independently develop and maintain cloud services and data platforms (preferred: Google Cloud Platform)
• Support the build-out of data products using Data Mesh (decentralized ownership; data products as standalone services)
• Design and implement stable backend services and REST/GraphQL interfaces for integration with applications and data environments
• Automate deployments and infrastructure with Infrastructure-as-Code; co-create stable, repeatable pipelines
• When needed, integrate AI/genAI services (e.g., LLM API) with data-driven applications
• Maintain high code and data quality via testing, Code Review, monitoring, and Continuous Integration
• Collaborate with cross-functional project teams and business areas; access experienced team experts for complex architecture

Requirements

• Completed higher education in computer science/Applied IT/STEM/engineering/math or equivalent technical qualifications
• Minimum 3 years of commercial or project experience in Software Engineering or Data Engineering, with documented independent implementation
• Practical experience with GCP (preferred) or AWS for creating and operating cloud solutions
• Experience with data products and Data Mesh; good understanding of scalable, reusable data services
• Very good Python skills
• Comfortable with Git, CI/CD, testing, and Code Review
• Polish + English or Polish + German communication at minimum B2

Benefits

• Partner-style collaboration with autonomy and a dialog culture in product teams
• Trust-based flexibility: no rigid working hours; focus on results
• Efficient onboarding with an implementation plan shared in advance