Data Engineer

🌍 Why this role exists Sortlist is an AI-powered marketplace connecting companies with top service providers in marketing, web & IT. We help thousands of businesses find the right partners faster. At Sortlist, data should align people around decisions — not trigger debates about metrics . We’re entering a new chapter for data. We’re moving from dashboard-centric analytics to a model-driven foundation where metrics are consistent, trusted, and scalable across teams. This evolution is key to unlocking real self-service analytics and, increasingly, AI-assisted workflows like text-to-SQL. We’re hiring someone excited by this transition — someone who wants to help define what modern BI looks like in a growing scale-up. You’ll join a small, experienced data team and work closely with Product, Finance, Growth, and Engineering to make data trusted, shared, and genuinely useful . 🔍 What you’ll do Design and evolve analytical data models that remain stable as the product and business evolve Challenge vague or poorly framed questions and turn them into clear, well-defined metrics Make the “right number” easy to find, understand, and trust — especially for: Financial performance Investment and prioritisation decisions Product focus and trade-offs Build and document data models that scale beyond you , enabling reliable self-service and AI-assisted analytics Play a key role in modernising our analytics tooling : Contribute to the transition toward more modern data consumption patterns Help ensure AI-assisted workflows can safely rely on strong, well-defined data models Participate in selecting, configuring, and improving the tools used by end users Dashboards may exist. Models and decisions are not optional. ⚙️ How you’ll work You focus on durability and rigour : models are testable, documented, and resilient to change You adapt your approach to how decisions are actually made — not how you wish they were made You communicate clearly with both technical and non-technical stakeholders You treat stakeholders as partners: you co-design metrics , you don’t just “take requirements” Strong opinions about data quality and modeling are not just welcome — they’re expected. 🚀 Why This Role Will Stretch You You don't need to have led a data transformation before. What matters is your ability to think critically about trade-offs, communicate across teams, and improve your judgment over time. This role will stretch your ability to: Think in systems — seeing how data decisions ripple across Product, Finance, and Growth Balance rigour with pragmatism — knowing when perfect is the enemy of good Influence without authority — building trust and co-designing metrics with stakeholders Shape tooling strategy — contributing to what modern BI looks like, not just using it If you're mid-level, you'll learn how to design durable data models and navigate ambiguous business problems. If you're senior, you'll sharpen your ability to drive consensus and make strategic trade-offs. 🔧 Current data stack & direction Today, our core stack includes: Warehouse : BigQuery Modeling layer : dbt BI / internal tools : Tableau, Retool This stack is intentionally evolving . We are actively transitioning toward more modern, model-driven analytics tooling , with a strong focus on: Reusable, well-defined data models Scalable self-service analytics AI-assisted data exploration built on solid foundations You will be a key contributor in shaping this transition — both technically and conceptually. 👤 Who we’re looking for This role is open to mid-level profiles and senior candidates , under freelance or employee contracts. You’ll thrive here if you: Are comfortable with ambiguity and incomplete problems Enjoy connecting data to real business and financial outcomes Are proactive and don’t wait for perfect instructions Care more about adoption and impact than ownership or control Like working with many different people and perspectives ... (truncated, view full listing at source)