Senior Data Engineer (Go)

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: • ETL Data Pipelines (Batch & Streaming) • Develop and operate ETL pipelines to extract, transform, and load data from multiple sources • Support both batch workloads (large-scale periodic data processing) and streaming workloads (real-time or near-real-time data flows) • Optimize performance, scalability, and reliability of data processing pipelines • Collaborate with data engineers and analysts to ensure high-quality, clean, and accessible datasets • ML Data Pipelines using Temporal • Design, implement, and maintain robust ML data pipelines for training, validation, and inference of machine learning models • Use Temporal for workflow orchestration, ensuring reliability, retries, and state management across complex ML workflows • Collaborate closely with ML engineers and researchers to automate and scale model pipelines • Ensure pipelines are reproducible, maintainable, and observable • Backend Services & Infrastructure • Design, build, and maintain backend services in Go  • Work with PostgreSQL and object storage (S3) to store and manage structured and unstructured data • Deploy and manage services using Kubernetes (K8s) and Helm • Implement best practices in CI/CD using GitHub Actions • Apply system design and data modeling principles, handling concurrency and performance optimization Requirements: • 3+ years of commercial experience in Go (most of which in a production setup with real customers) • Strong knowledge of ETL pipeline development (batch and streaming workloads) • Experience with Temporal or other asynchronous workflow orchestration tools • Experience with PostgreSQL and object storage (S3) • Familiarity with Kubernetes (K8s) and Helm • Understanding of concurrency patterns and performance optimization in Go • Experience building and operating ML data pipelines is highly desirable • Strong collaboration skills and attention to detail Nice to Have: • Experience designing APIs/SDKs • Experience with complex migrations or data model changes • Knowledge of TDD, DDD, or other development best practices • Familiarity with resiliency patterns (retries, circuit breakers) • Experience integrating backend systems with ML models • Experience with OpenFGA or similar tools • Familiarity with stakeholder management and brief, concise communication Technology Stack: • Core Backend: Python (FastAPI), Go • Data Storage: PostgreSQL, S3 / object storage • Workflow Orchestration: Temporal (for ML pipelines) • ETL: Batch and streaming pipelines • DevOps & Infrastructure: Kubernetes (K8s), Helm, GitHub Actions • Internal Tools: TypeScript / Nx for CLI automation (if applicable)