Who we are: Ceres is leading the way in clean energy innovation, pioneering advancements in electrolysis for green hydrogen production and fuel cells for future power solutions. With our dynamic licensing model, we've built powerful partnerships with major multinational companies like Bosch, Doosan, Shell, and Weichai and our solid oxide platform is transforming energy systems, delivering high-efficiency green hydrogen to decarbonise some of the most emissions-heavy industries including steelmaking, and future fuels. At Ceres, we foster a workplace driven by passion and purpose. We support our team to think ambitiously, collaborate creatively and confront complex challenges directly. Innovation is at the core of who we are, and we strive to push the boundaries of what’s possible with technology. Purpose of the role: This role sits within the department of Modelling and Digitalisation, consisting of highly skilled and dedicated modelling and simulation engineers, data scientists, and data engineers. The department specialises in advanced multi-domain computational modelling, data analysis, and creates bespoke data products and cloud data platform solutions to support all core areas of the business, with a focus on accelerating the company’s product and technology development. The purpose of this role is to enable and support the Data Product Team to design and deploy data applications built on our Azure Databricks platform to improve data accessibility, robustness and connectivity, enabling data analytics and data driven decisions to be made across the business. Key Accountabilities: Take ownership of data products throughout their entire lifecycle, from ideation and design to deployment, maintenance, and eventual deprecation to support data-driven decision making and analytics. Act as the primary point of contact for the assigned data product, addressing both technical and business needs. Work closely with cross-functional teams including data scientists, analysts, and software engineers to deliver high-value data products. Collaborate with stakeholders to understand business requirements and translate them into data product specifications. Ensure data products meet performance, scalability, and reliability standards Act as a liaison between technical and non-technical stakeholders to align on product objectives and deliverables. Monitor the performance and reliability of data products in production environments. Monitor and address data quality issues proactively. Provide technical guidance and mentoring to team members as needed. Knowledge and skills required for the role: Bachelor’s degree in computer science, data science, engineering, or a related STEM field Several years of experience in data product development, or related fields, with a proven track record of delivering high-quality data solutions Advanced degrees (e.g., Master’s or Ph.D.) in relevant fields are a plus but not mandatory Expertise in programming languages such as Python and SQL Familiarity with scripting for automation and process optimisation Knowledge of cloud environments like Microsoft Azure, AWS or Google Cloud Platform Experience with cloud-native data tools (e.g. Databricks, AWS Glue, Google Big Query) Experience in supporting BI tools like Tableau, Power BI, or Looker Ability to interpret data for actionable insights and collaborate with analysts Ability to work in cross-functional Agile teams, collaborating closely with data engineers, product managers, and other stakeholders Strong understanding of Agile methodologies (e.g., Scrum, Kanban) and their application in data product engineering projects Knowledge of DevOps practices, including infrastructure as code, continuous integration/continuous delivery (CI/CD), and containerization (e.g., Docker, Kubernetes) Experience working within Agile workflows and familiarity with Agile principles, ceremonies (e.g., stand-ups, retrospectives) Fast learner of new domain knowledge, with awareness of fuel cell technology a plus Excellent interpersonal skills to work effectively with cross-functional teams Ability to mentor junior engineers and guide technical decisions