Help design, build and continuously improve the clients online platform
Research, suggest and implement new technology solutions following best practices/standards
Take responsibility for the resiliency and availability of different products
Be a productive member of the team.
Requirements
Bringing 5+ years of hands-on experience in Data Engineering and MLOps, with a strong foundation in cloud infrastructure, software engineering best practices, and machine learning operations.
Proven experience in cloud engineering with AWS, including infrastructure setup and management
Strong Data Engineering capabilities, including building batch data jobs and designing robust ETL pipelines
Solid Software Engineering background, with experience in software design, test development, and applying engineering best practices
Proficient in Python, Docker, Git, and CI/CD pipelines, with a strong DevOps mindset
Hands-on experience with MLOps tools such as Airflow, MLflow, and similar platforms to support scalable model deployment and monitoring
Enthusiastic about both building and maintaining production-grade solutions
Comfortable working in Agile environments, collaborating across cross-functional teams
Passionate about the energy transition and contributing to the development of complex systems driving sustainable change
Benefits
A challenging, innovating environment.
Opportunities for learning where needed.