My co-founder Ian and I combine over 15 years of industry experience, working with companies like SEW-Eurodrive, Terex, Bosch and Carl Zeiss. We co-founded Resourcly, a Project A-backed, industrial tech start-up to help industrial manufacturers streamline complex portfolios to improve EBIT while preventing and reducing idle inventory from being scrapped.
With our solution, we want to solve industry problems that we have tried to address for the last decade in the manufacturing companies we worked for, but that have so far been out of reach. With new technology and AI, that can finally happen.
Complex processes and products, lack of engineering talent and massive labour costs as well as a lack of intelligent automation have remained the industry's most pressing challenge. With LLMs and agents, we finally have the tools to solve this.
Our vision is that future purchasing and engineering processes will be orchestrated and run by an AI workforce - ensuring reliable and cost-efficient procurement and flow of goods in an uncertain and complicated world with finite resources.
Our goal is to build a small, but excellent team, therefore we are looking for a Business Intelligence Engineer. If you are excited to work in a very early-stage environment alongside the founding team, building the data foundation the whole company steers by, using data to drive better decisions - please reach out.
As our Business Intelligence Engineer, you will build, own, and evolve Resourcly's internal data applications and BI infrastructure, and use it to improve the company's basis for decision-making. Your mission is to drive Resourcly toward becoming a fully data-driven organization that knows where it's winning, where it's leaking value, and what to do next.
This is not a back-office reporting role. You will be the first dedicated hire for internal analytics, which means you'll shape the data stack, modelling conventions, and BI tooling from the ground up rather than inherit them. You'll work closely with our COO & Co-Founder, alongside Engineering, Sales, Customer Success, and Product, giving you visibility into how every part of the business runs on data from day one. The role demands a rare combination: genuine excellence in data engineering paired with the business judgment to understand context, ask the right questions, and translate numbers into direction leadership can act on.