Senior Data Engineer at Vizzia

🎯 MISSION Vizzia develops technology solutions with strong societal impact, combining artificial intelligence and field observation to better understand and manage environmental challenges. We are looking for a Senior Data Engineer to optimize, secure, and industrialize the data pipelines powering our AI products. Your role is critical: you ensure the quality, availability, and performance of the data used daily by AI, Product, and DevOps teams. 🛠 RESPONSIBILITIES - Design, develop, and maintain robust, automated, and scalable data pipelines. - Ensure data quality, security, and reliability throughout the entire data lifecycle. - Define and maintain infrastructure as code for data-related services. - Build and maintain dashboards, monitoring tools, and reports for internal teams. - Work closely with Data Science, DevOps, and Product teams to ensure data consistency and value. - Monitor and optimize performance using observability tools (Datadog, Grafana, Prometheus). ✅ PROFILE TECHNICAL SKILLS - Master’s degree (or equivalent) in computer science, data engineering, or AI. - 5+ years of experience in Data Engineering, ideally in cloud and AI-driven environments. - Excellent command of Python and software engineering best practices (testing, versioning, packaging). - Strong knowledge of SQL and NoSQL databases (PostgreSQL, DynamoDB). - Solid experience with workflow automation (Airflow, GitHub Actions, GitLab CI/CD). - Strong understanding of MLOps concepts, data integration into ML workflows, monitoring, and deployment. - Cloud experience on AWS or GCP (S3, Lambda, RDS, Step Functions). - Knowledge of Docker and containerized environments. SOFT SKILLS - Strong technical rigor and constant focus on quality. - High level of autonomy and ability to own a broad scope. - Clear, structured communication with a collaborative mindset. - Ability to work with cross-functional teams. - Analytical mindset and attention to detail. ⭐ WHAT WILL MAKE THE DIFFERENCE - Proven experience running critical production data pipelines. - Advanced practice of data observability (logs, metrics, alerting). - Open-source contributions in the data or ML ecosystem. - Proactive approach to continuous improvement of data workflows and environments. - Sensitivity to the environmental or societal impact of technology. 🧰 TECH STACK - Languages: Python - Databases: PostgreSQL, DynamoDB - Pipelines: GitHub Actions - Cloud: AWS (S3, Lambda, RDS, Step Functions), GCP - Containerization: Docker - Observability: Datadog, Grafana, Prometheus - MLOps: MLflow, SageMaker Benefits 🏡 Hybrid work 🏝 “Contrat cadre” and RTT (between 8-12 per year depending on the number of public holidays in the current year) 💻 A Mac or PC depending on your preferences 💸 BSPCE 🍜 60% coverage of meal vouchers worth €9 per worked day 🚃/🚲 Sustainable mobility allowance 🏥 Mutuelle (Alan) 💼 Offices located in central Paris (9th arrondissement) ☀️ Annual offsite with the whole team and plenty of company events