Data Engineer

About the role

Help us make a big green dent in the universe. We're on a mission to drive the global renewable energy revolution, and we need many more people to help us make our vision a reality. Octopus Energy Generation (OEGEN) is a leader in sourcing, investing in, and managing a wide range of utility-scale renewable energy assets. As we continue to expand our investment base, we are dedicated to building a diverse team that reflects the communities we serve. Currently, we manage a global portfolio of over £8 billion in renewable energy assets. We are committed to delivering best-in-class responsible investment activity, offering like-minded investors the means and products to invest their capital sustainably. It is our ambition to change the entire energy lifecycle and make every green electron matter, delivering the best outcomes for customers, investors, the environment and society, accelerating the transition to net zero. OEGEN Data, Tech & Transformation Team We are embarking on a comprehensive transformation program designed to drive significant advancements in our business operations and technology landscape. Our primary goal is to transition from our current reliance on legacy systems and specialized off-the-shelf tools to a more integrated, AI-driven, and data-centric operational model. Leveraging insights and guidance from our other technically mature entities like Kraken and OE, we plan to adopt cutting-edge tools and capabilities, particularly in AI and Python-driven solutions. By investing in a diverse range of skills, we aim to create a hybrid team capable of operating in both our legacy and future environments, ultimately transforming OEGEN into an efficient, data-driven organization. About the role We’re looking for a Data Engineer who can own the journey of data from source systems to decision-ready outputs. You’ll build and maintain pipelines, model data, stand up dashboards, and integrate systems via APIs. In a team this size, you’ll also get involved in application development - building internal tools with Streamlit, FastAPI, or HTMX that put data directly in the hands of our investment and asset management teams. In your first 3 months you’ll have taken ownership of at least one critical pipeline from an external system into Databricks, and built or materially improved a reporting layer used by Fund Management or Asset Management. What you'll do Design, build, and maintain scalable data pipelines in Databricks, ensuring data is reliable, timely, and well-documented. Own and evolve our Databricks models - define schemas, enforce testing, and keep the warehouse clean. Automate manual data processes using Python, replacing spreadsheets and ad-hoc workflows with robust, repeatable jobs. Build performance dashboards and reports in Streamlit and HTMX (FastAPI) that Finance, Asset Management, and Fund Management actually use. Integrate internal and third-party systems via REST APIs, improving data accessibility across the business. Champion data quality - implement validation, monitoring, and governance practices that give stakeholders confidence in the numbers. Collaborate directly with non-technical teams to understand their problems and translate them into data solutions. What you'll need Strong SQL and Python skills, used daily for pipeline development, data modelling, and automation. Experience with modern data stack tooling: a cloud data platform (Databricks preferred), and version control (Git/GitHub). A solid understanding of data modelling, warehousing patterns, and ETL/ELT design. To be comfortable working with Postgres or similar relational databases. Clear communication - you can explain a data model to a fund manager and discuss trade-offs with an engineer. A bias toward shipping: you’d rather get something working and iterate than spend weeks in design. Bonus points for Full-stack development experience - particularly with Streamlit, FastAPI, or HTMX. Experience buildin

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