Junior Research Associate – Data Engineer
Job TitleJunior Research Associate – Data Engineer
The CMCC Foundation is a scientific research center on climate change and its interactions with the environment, the society, the world of business and policy makers.
Our work aims to stimulate sustainable growth, protect the environment and develop strategies for the adaptation and mitigation of climate change.
Our Division of Advanced Scientific Computing (ASC) is looking is looking to hire one talented, motivated, and proactive Data Engineer whose main responsibilities will be:
- to build, deploy and maintain CMCC Data Management and Analytics Platform;
- to build automation systems and tools for configuration, monitoring, and orchestration of data infrastructure and data pipelines;
- to support Data Scientists with environments for development and operationalization of Data Analytics applications and AI/ML models.
The job location is CMCC Headquarters or Site in LECCE, Italy. Remote working is considered as an option only from european sites.
(Deadline: May 20, 2023)
- No telecommuting
- No Agencies Please
We are looking for a motivated person with the following requirements:
- Master’s degree in computer science or software engineering or equivalent fields.
- 3+ years of experience as Data Engineer, DataOps and/or DevOps.
- Experience with Data Flow Automation (Prefect, Airflow, …).
- Experience with SQL and NoSQL Databases (PostgreSQL, MongoDB, …).
- Experience with containerization and container orchestration (Docker, Kubernetes, …).
- Experience with agile software development in Python.
- Experience with CI/CD tools (GitHub actions, Jenkins, …)
- Excellent problem-solving and troubleshooting skills.
- Ability to work both independently and in a team.
- Proficient verbal and written communication skills in English.
- Experience with management of large volume datasets related to climate and geoscience;
- Familiarity with Python frameworks for scientific data analysis (numpy, scipy, pandas, xarray, …) and ML/AI model development (PyTorch, TensorFlow, …);
- Experience with platforms for management of ML workflows (Kubeflow, MLflow, …).