Software Engineer

Job Title: Software Developer Location: Exeter (with hybrid working) SC Cleared Job Summary: We are seeking a Software Developer to join our dynamic Observations Research & Development Technology team. In this role, you will directly contribute to global and national sensor networks that collect crucial data, enabling our world-class forecasting models and cutting-edge research. You will work closely with a collaborative DevOps team, developing and maintaining systems that handle vast amounts of critical data. Key Responsibilities: Design & Implement Solutions: Develop and maintain modern, cloud-based systems for processing, storing, and distributing high-volume observational data from global sensor networks. Collaboration: Work in a hybrid environment, collaborating with cross-functional teams and participating in key team activities at our Exeter HQ. Data Processing & Distribution: Ensure data from sensor systems is efficiently managed and distributed, supporting vital weather forecasting and research. Optimize Systems: Focus on optimizing the balance between storage and compute costs for long-term data management. Support DevOps: Contribute to the DevOps team’s efforts in automating workflows and improving the efficiency of data pipelines. Essential Skills & Qualifications: Experience with Cloud Platforms: Practical experience in modern cloud environments (e.g., AWS) for data storage and processing. Programming Skills: Proficiency in programming languages such as Python / Java, with a focus on data handling and system integration. DevOps Familiarity: Understanding of DevOps tools like Docker, Kubernetes, and Jenkins. Database Management: Experience with SQL or NoSQL databases, and familiarity with data lifecycle management practices. Collaboration Skills: Ability to work in a hybrid, collaborative team environment, both remotely and on-site. Desirable Skills: Experience with high-performance data systems. Knowledge of weather or environmental data systems. Familiarity with sensor technologies and observational networks