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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Capital on Tap - **Location:** London, UK - **Salary:** £71,612.0 - **Contract:** Permanent contract - **Skills:** Data Analysis, Automation of Tests, Continuous Integration, Data as a Services, Data Auditing, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Transformation, Data Security, Data Systems, Data Warehousing, Github, Python (Programming Language), Machine Learning, Backup and Restore, Scripting, Snowflake, Kubernetes, Data Management, Dynamic Data, Data Delivery, Software Version Control, Data Pipelines, Api Management - **Published:** August 20, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5848437988 ## About the Role * Proven experience as a Data Engineer, designing, building, and maintaining scalable data platforms and pipelines. * Deep experience with Snowflake, including advanced features like dynamic data masking, row-level security, data backups, and ELT tools. * Strong Python skills for data engineering, scripting, and automation. * Strong SQL performance, with a solid understanding of data warehousing concepts. * Demonstrated experience with GitHub, CI/CD, and collaborative development. * Strong stakeholder management and communication skills, comfortable working with technical and non-technical colleagues. * Experience in kubernetes, datadog and ML model deployments are great to have. ## Description The Data Platform team is responsible for designing, building, maintaining, and optimising our modern data platforms and infrastructure. Our main goal is to ensure the organisation has seamless access to high-quality, reliable, and performant data, from ingestion through to consumption by various teams. We work on key projects involving data pipeline development, platform management, model training and deployment, data quality assurance and customised data tooling., * Design, build, and maintain scalable and resilient data pipelines and infrastructure, using Python for custom data transformations, API integrations, and orchestration. * Implement and manage data platforms leveraging Kubernetes for efficient deployment, orchestration, and scaling of data services and applications. * Own the flow and security of data in our Snowflake data warehouse, ensuring optimal data delivery architecture and availability for global business operations and data science work. * Build CI/CD pipelines using GitHub for automated testing, deployment, and version control. * Collaborate with stakeholders across Engineering, Data Science, and Analytics Engineering to gather requirements and deliver high-impact data solutions. * Ensure data quality, reliability, and observability across the platform through robust monitoring, alerting, and testing frameworks. Our Values & Culture * Just Pilot: We never settle for "good enough". We pilot new ideas fast, ask questions to figure it out, and scale quickly. * Why Not Today? Fast is as slow as we go - speed and simplicity gives us a competitive advantage. * Be a Buddy: We tap in from day one to help the team, we do the right thing even if it's hard. * Owners and Dates: We don't chase people. If you own a task and agree to a date, the expectation is that it gets done. * Feedback: We want our employees to flourish, so we regularly provide direct and constructive feedback. ## 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) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [JavaScript? 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