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# Senior Software Engineer - Data Technologies, Non-Securitised Data - Macro & Industries

- **Company:** Bloomberg
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Big Data, Software Quality, Continuous Integration, Extract Transform Load (ETL), Data Systems, Machine Learning, Data Streaming, Backend, Event Driven Architecture, Information Technology, Apache Kafka, Data Pipelines
- **Published:** September 27, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/senior-software-engineer-data-technologies-non-securitised-data-macro-industries/48668916

## About the Role

graph.We value incremental delivery over big-bang releases. Getting our work into the hands of users early helps ensure we are building what the business needs. We foster a culture of psychological safety, collaboration, and continuous learning, where it's safe to ask questions, challenge ideas, and support each other to deliver under pressure.ResponsibilitiesTake ownership of projects and drive them from design through to deliveryBuild robust, scalable data pipelines that process large volumes of complex data reliablyIdentify recurring problems across domains and build reusable solutions that benefit multiple teamsDevelop strong working relationships with engineering peers, data teams, and business stakeholdersChampion engineering best practices, writing well-tested, maintainable, and high-quality codeDeliver incrementally in a fast-paced environment, prioritising thoughtfully across competing workstreamsRequirementsStrong backend experience with PythonA degree in Computer Science,
Engineering, Mathematics, a similar field of study, or equivalent work experienceExperience building and maintaining data pipelines or ETL workflowsGood system design and architecture skillsExperience working with large distributed systemsExperience of working with Kafka pipesExperience of working with high volume, high throughput, scalable data pipelinesExperience working with big data pipelines and storesAn understanding of continuous integration principles and writing testable codeNice-to-HavesExperience integrating AI or machine learning into data pipelines or developer toolingA track record of leveraging AI to improve personal or team productivityFamiliarity with event-driven architectures and message-based data processingExperience with data modelling or schema designComfort working with diverse groups of stakeholders, both technical and non-technicalA desire to get involved in department and company-wide initiatives #J-18808-Ljbffr

## Description

infrastructure teams, contributing application-level insights that help guide platform improvements and influence infrastructure strategy. The breadth of domains we support gives you exposure to a broad and varied problem space.We care deeply about engineering craft. We build reusable components and shared libraries that solve cross-domain problems, abstracting away complexity so that common patterns are handled well in one place rather than duplicated across pipelines. We look for recurring challenges and invest in building tools that improve reliability, reduce risk, and make our teams more productive. This mindset means we are always looking for opportunities to raise the bar on performance, code quality, and maintainability.We are actively exploring how agentic and generative AI can augment our data workflows to improve data coverage and quality. We are also contributing to Bloomberg's semantic data initiatives, helping define how data flows into Bloomberg's enterprise knowledge


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