We are a leading European AI company developing large language models and generative platforms for enterprise and government clients.
Our products combine high-performance technologies, data security, and transparency, fully aligned with European regulatory and ethical standards.
As a Data Engineer, you will design, build, and maintain high-performance backend services and data pipelines, enabling our teams to deliver scalable, reliable, and production-ready systems.
Responsibilities:
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** ETL Data Pipelines (Batch & Streaming)**
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Develop and operate ETL pipelines to extract, transform, and load data from multiple sources
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Support both batch workloads (large-scale periodic data processing) and streaming** **workloads (real-time or near-real-time data flows)
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Optimize performance, scalability, and reliability of data processing pipelines
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Collaborate with data engineers and analysts to ensure high-quality, clean, and accessible datasets
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** ML Data Pipelines using **Temporal
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Design, implement, and maintain robust ML data pipelines for training, validation, and inference of machine learning models
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Use **Temporal or similar tools **for workflow orchestration, ensuring reliability, retries, and state management across complex ML workflows
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Collaborate closely with ML engineers and researchers to automate and scale model pipelines
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Ensure pipelines are reproducible, maintainable, and observable
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** Backend Services & Infrastructure**
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Design, build, and maintain backend services in **Go **or **Python **
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Work with PostgreSQL and object storage (S3) to store and manage structured and unstructured data
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Deploy and manage services using** Kubernetes (K8s)** and** Helm**
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Implement best practices in CI/CD using GitHub Actions
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Apply system design and data modeling principles, handling concurrency and performance optimization
Requirements:
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2-3+ years of commercial experience in** Go or/and proficient in Python** (most of which in a production setup with real customers)
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Strong knowledge of ETL pipeline development (batch and streaming workloads)
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Experience with Temporal or other asynchronous workflow orchestration tools
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Experience with PostgreSQL and object storage (S3)
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Familiarity with Kubernetes (K8s) and Helm
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Understanding of concurrency patterns and performance optimization in Go
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Experience building and operating **ML data pipelines **is highly desirable
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Strong collaboration skills and attention to detail
Nice to Have:
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Experience designing APIs/SDKs
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Experience with complex migrations or data model changes
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Knowledge of TDD, DDD, or other development best practices
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Familiarity with resiliency patterns (retries, circuit breakers)
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Experience integrating backend systems with ML models
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Experience with OpenFGA or similar tools
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Familiarity with stakeholder management and brief, concise communication
Technology Stack:
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Core Backend: Python (FastAPI), Go
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Data Storage: PostgreSQL, S3 / object storage
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Workflow Orchestration: Temporal (for ML pipelines)
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ETL: Batch and streaming pipelines
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DevOps & Infrastructure: Kubernetes (K8s), Helm, GitHub Actions
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Internal Tools: TypeScript / Nx for CLI automation (if applicable)
We offer:*
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Flexible working format - remote, office-based or flexible
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A competitive salary and good compensation package
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Personalized career growth
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Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
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Active tech communities with regular knowledge sharing
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Education reimbursement
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Memorable anniversary presents
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Corporate events and team buildings
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Other location-specific benefits
*not applicable for freelancers