> Markdown version of [/jobs/ext/2795674-senior-data-engineer](https://www.wearedevelopers.com/jobs/ext/2795674-senior-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** IWSR - **Location:** London, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Microsoft Excel, Artificial Intelligence, Amazon Web Services, Databases, Cursor (Graphical User Interface Elements), Programming Tools, Python (Programming Language), Microsoft SQL Server, Data Ingestion, Pyspark, Production Code, Data Pipelines, Databricks - **Published:** September 8, 2026 - **Apply:** https://www.collegerecruiter.com/job/2840676169-senior-data-engineer ## About the Role We care less about your CV checklist and more about how you work. The strongest candidates tend to: * Think in problems, not just technologies - "here's what was broken and here's how I fixed it" * Be comfortable inheriting messy, real-world systems rather than always building green field * Have worked in small teams where you had to figure it out yourself - no dedicated platform team, no safety net * Show an engineering mindset: careful, methodical, aware of what goes wrong in production Technically, you'll need solid Python (data pipelines, production code), hands-on SQL Server experience, and genuine Databricks / PySpark exposure. AWS familiarity and comfort with AI-assisted dev tools (Copilot, Cursor, Claude Code) are a plus. If you've ever built something a bit scrappy to solve a real problem, a quick front end, a workaround that became the system, we'd like to hear from you. ## Description * Owning and improving the data ingestion pipeline that powers our Global Database * Leading the migration of Excel-based processes into production Python * Collaborating on Databricks migration work (GTR and data pooling) * Taking charge of our SQL Server environment, security, structure, day-to-day management * Working directly with non-technical stakeholders to translate data problems into business outcomes ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Where To Find Software Engineering Jobs](https://www.wearedevelopers.com/magazine/396-where-to-find-software-engineering-jobs)