Our purpose 🌍

Inspiring and empowering our people to create a positive difference for themselves, our clients and the planet.

Sustainable Energy First is an energy and sustainability consultancy, founded to solve energy management problems in very large, complex commercial estates.

This remains the core of our business driven by a commitment to sustainability and the goal of reducing our clients' carbon footprint.

The Role in a Nutshell 🐿️

This role will provide dedicated data engineering capability within the Data Analytics & Intelligence team, with a primary focus on developing and optimising our use of Microsoft Fabric. The team has already begun establishing capability in Fabric alongside ongoing delivery. This role will build on that foundation - designing and implementing scalable data pipelines, reusable data models, and robust engineering patterns that support both current delivery and future growth. You will play a key role in moving us from project-based builds towards a more structured, platform-led approach to data.

Alongside platform development, you will also work across the whole business to improve how data is collected, stored, and managed. This includes reducing reliance on manual spreadsheets, supporting the evolution of our SQL-based database in collaboration with the in-house development team, and helping embed more consistent, well-governed data practices across teams. Where new data requirements are identified, you will take ownership of how that data is ingested, structured, and stored - ensuring it is set up in a way that supports scalable, long-term use across the business.

You will be central to strengthening our data foundations, enabling the BI and analytics teams to deliver faster, more reliable insight, and ensuring that data is structured in a way that is scalable, maintainable, and aligned with business needs.

Requirements

• Scalable Data Platform in Microsoft Fabric - Design and implement robust, scalable data pipelines and models within Microsoft Fabric that support consistent ingestion, transformation, and storage of data from across the business.
• Efficient and Automated Data Processing - Leverage Fabric capabilities (including notebooks and pipelines) to enable efficient, repeatable, and automated data processing, reducing manual effort and improving reliability.
• Structured and Accessible Business Data - Define and improve how data is collected, stored, and structured across the organisation, ensuring it is consistent, well-organised, and accessible for reporting, analytics, and operational use.
• End-to-End Ownership of New Data Sources - When new data requirements are identified, design and implement the appropriate ingestion pipelines, storage structures, and data models - ensuring new data is captured and integrated in a way that supports scalable, long-term use.
• Reduced Reliance on Manual Processes - Support the transition away from spreadsheet-driven workflows by delivering automated, governed data solutions that improve efficiency, accuracy, and consistency.
• Strong and Evolving Data Foundations - Work with the in-house development team to support and enhance the SQL-based core database, ensuring it integrates effectively with the wider data platform.
• Improved Data Governance and Quality - Strengthen data governance, quality, and consistency across the business by embedding good practices in how data is managed, transformed, and used.