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# Remote Senior Data Engineer (AWS)

- **Company:** Codat
- **Location:** Barnsley, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Training Data, Artificial Intelligence, Airflow, Amazon Web Services, Code Generation, Data Validation, Python (Programming Language), Software Tools, SQL Databases, Workflow Management Systems, Apache Spark, Data Layers, Data Lakes, Production Code, Data Management, Data Pipelines, Databricks
- **Published:** October 5, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/remote-senior-data-engineer-aws/50546426

## About the Role

and find opportunities to apply it across our products and pipelines where it delivers real value, from research and prototyping through to more operational uses such as agents that help diagnose and fix pipeline issues. Help lay the foundations for our emerging MCP and semantic layer, so our data becomes something both people and AI systems can query and reason over. Strong software engineering fundamentals: you write well-tested, production-ready Python and care about maintainability, observability, and operational excellence. A track record of building data pipelines and production systems from the ground up, rather than mainly configuring managed services or wiring off-the-shelf tools together. Solid experience with modern data engineering tools and patterns, with real depth in several of SQL, Spark, Databricks/Delta Lake, orchestration tools (Dagster, Airflow, Temporal), and dbt. Comfort with modern deployment practices: It's a bonus if you've shaped these for a team, not only
worked within them. You're comfortable pushing back or proposing a different approach when your read of the data and the domain calls for it. AI as a default part of how you work, with evidence of real efficiency gains and creative use beyond code generation, such as research, building domain knowledge, or prototyping. Nice to have: exposure to the building blocks of AI-ready data, such as semantic layers, ontologies, or text-to-SQL, plus any experience applying AI operationally within data platforms or pipelines. This won't be your main focus, but it will help as our platform grows to support an MCP. Please note, this role is remote - UK only and we cannot provide sponsorship for this position.

## Description

operational reliability as you do about getting things shipped. You'll do all of this while staying close to the code: it'll suit you if you want to keep building hands-on, rather than move into pure architecture or people management in the near term. Write production code every day, most likely in Python, building and maintaining the data pipelines that power our Insights products. Own the full lifecycle of your projects, from understanding the data domain through to pragmatic design, shipping, and keeping things running reliably in production. Set and lead the technical direction of the Insights platform, and communicate it openly across engineering and the wider business, so product and commercial colleagues understand the choices you are making and why. Help raise engineering standards across the team and improve technical quality through strong engineering practice, including testing, observability, data quality checks, and clean, maintainable code. Make AI your default way of working


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