Senior Azure Data Engineer, Greenomy

• Solid proficiency in Python (5years+), with a focus on writing clean, efficient, and production-ready code. Experience with authentication, role-based access control, etc
• Hands-on experience with Azure services, specifically tailored towards machine learning and data management. This includes but is not limited to Azure Machine Learning, Azure Databricks, Azure Data Factory, and Azure Kubernetes Service (AKS)
• Strong analytical and problem solving skills and excellent organization and time management
• Experience designing and managing ETL processes, optimizing data storage solutions, and integrating diverse data sources. Should be comfortable working with both structured and unstructured data sets in Azure environments
• Demonstrated ability in deploying, monitoring, and maintaining machine learning models in production environments. Familiarity with containerization tools like Docker and orchestration platforms, especially Kubernetes, is very important
• Proficient in use of Git for version control, with a deep understanding of CI/CD processes, particularly as they relate to machine learning and data engineering workflows
• Library & Framework Experience:Experience designing and managing ETL processes, optimizing data storage solutions, and integrating diverse data sources. Should be comfortable working with both structured and unstructured data sets in Azure environments. Practical knowledge refactoring and deploying ML models with an emphasis on generative AI techniques and models
• Fluent English (written and spoken)

Desirable

• As a senior Data Engineer you will be a critical part of our dedicated team of data science specialists
• You will define the architecture for and build the pipelines and infrastructure that will be the basis for robust and production-ready solutions to enhance the AI capabilities of our ESG reporting software
• Bring POCs developed by our Data Scientists to production
• Write and deploy state of the art APIs serving our data science services
• Design & implement python-based architectures for interaction between our SaaS platform (written in NodeJS & Mongo, owned by our engineering team) and data science services (written in python, owned by the data science team)
• Together with our cloud infrastructure team own deployment of Data Science services and our azure-based data platform.