> Markdown version of [/jobs/ext/338327-data-engineer-fraud](https://www.wearedevelopers.com/jobs/ext/338327-data-engineer-fraud). 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). --- # Data Engineer, Fraud - **Company:** Xcelirate - **Location:** London, UK (Remote available) - **Experience:** Experienced - **Salary:** £98,000.0 - **Contract:** Permanent contract - **Skills:** Airflow, Data Analysis, Databases, Continuous Integration, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Relational Databases, Database Design, Fraud Prevention and Detection, Python (Programming Language), Machine Learning, MySQL, Operational Databases, Query Optimization, SQL Databases, Tableau (Software), Data Storage Technologies, Feature Engineering, Flask (Web Framework), Reliability of Systems, Fastapi, Machine Learning Operations, Vertica, Data Pipelines - **Published:** June 10, 2026 - **Apply:** https://uk.indeed.com/viewjob?jk=8a4a53eac12e1aa2 ## About the Role Do you have experience in Tableau?, Do you have a Bachelor's degree?, * 3+ years of experience as a data engineer with some expertise in fraud detection systems or similar * Proficiency in Python and SQL, with knowledge of orchestration and transformation tools (e.g., Apache Airflow, DBT) * Strong knowledge of database design, query optimisation, and ETL/ELT workflows, ideally including relational databases such as MySQL and columnar databases such as ClickHouse * Experience building and maintaining production data pipelines * Familiarity with leveraging machine learning models, primarily as a component of the broader data pipeline, including model registries such as MLflow * Understanding of CI/CD processes for data pipelines * Hands-on experience with data visualization platforms for trend reporting (e.g., Tableau, Superset, Metabase) * Ability to support with model serving components, such as Flask or FastAPI * Familiarity with statistical techniques for fraud trend analysis and reporting * Experience with Git and version control in collaborative workflows ## Description The Data Engineer will focus on designing, developing, and maintaining robust data infrastructure to support use cases such as fraud detection but also general data engineering. The position emphasizes building scalable, high-performing data pipelines and storage systems for fraud use cases. Although this role involves light integration with machine learning models, its primary responsibility is creating the technical foundation that powers such use cases of fraud detection, analytics and reporting. What will you be doing? * Develop and Maintain Pipelines: build and maintain efficient, scalable data pipelines for use cases such as fraud detection * Support Fraud Analytics: enable analysts and product teams to identify and address emerging fraud patterns through engineered datasets * Integrate Detection Models: collaborate with teams to operationalise external fraud detection models and integrate them into the data infrastructure * Data Storage Optimisation: design and optimise data storage solutions for analysing fraud signals and managing historical data * Feature Engineering: create fraud-specific datasets and features to enhance detection accuracy while supporting business and analytics teams * Pipeline Monitoring and Optimisation: monitor fraud data pipelines to ensure system reliability and troubleshoot performance issues * Best Practices Documentation: establish and document best practices for fraud-related data engineering * Cross-Team Collaboration: partner with data, product, and engineering teams to proactively address fraud trends ## Related Videos - [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) - [Intro to FastAPI](https://www.wearedevelopers.com/videos/462-intro-to-fastapi) - [MySQL Protocol Features You Should Be Aware Of](https://www.wearedevelopers.com/videos/100267-mysql-protocol-features-you-should-be-aware-of) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Building and Deploying Multi-Agent Systems with ADK and Vertex AI](https://www.wearedevelopers.com/videos/1918-building-and-deploying-multi-agent-systems-with-adk-and-vertex-ai) - [Coding for Good: Achieving social change with an app](https://www.wearedevelopers.com/videos/1645-coding-for-good-achieving-social-change-with-an-app) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Software Engineer Salary London](https://www.wearedevelopers.com/magazine/252-software-engineer-salary-london)