# Engineering Manager – Data Platform [Yuno](https://gurify.com/jobs?q=Yuno) · London · Posted 4 months ago Full-time [Engineering Manager](https://gurify.com/jobs/engineering-manager) [Apply on the original posting → (opens in a new tab)](https://jobs.lever.co/yuno/0bb7b2d1-d208-4cd0-b650-5b924b8e5c96/apply) ## Job description Remote, Europe · Full Time · Experienced Engineering Manager · +6 Years of Experience Who We Are At Yuno, we are building the payment infrastructure that allows all companies to participate in the global market. Founded by seasoned experts from the payments and tech industries — including the team behind Rappi, one of Latin America's most ambitious tech companies — our technology provides access to leading payment capabilities, enabling companies to engage customers confidently and maintain global operations through seamless integrations. We empower high-performing teams at brands like InDrive, McDonald's, Rappi, and Viva Aerobus to connect to 300+ payment methods worldwide via a single API. By leveraging advanced AI and the latest technologies, we orchestrate smart routing and fraud prevention across 80+ countries. About The Role We are orchestrating a high-performing data team that works with pace and enthusiasm! Yuno moves money across borders for companies that can't afford for payments to fail. Our data platform is what makes that visible — to our product teams, our clients, and ourselves. As an Engineering Manager within the Data team, you will lead a team of data engineers responsible for the platform that processes billions of payment events across 80+ countries. You will own both the people strategy and set technical direction for your team that sits at the core of Yuno's business: enabling fraud detection, revenue analytics, payment optimization, and data-driven product decisions. You will operate in a fast-moving, global environment where data is mission-critical. Your Contribution Will Be Team Leadership Lead and develop a multidisciplinary data engineering team, fostering a culture of technical excellence, ownership, and continuous improvement. Mentor engineers at all levels — supporting their growth through coaching, structured feedback, and clear career expectations. Drive hiring processes to attract and retain top data engineering talent globally. Create an environment where engineers are empowered to take ownership and deliver with autonomy and pace. Technical Ownership Own the full lifecycle for your team — from ingestion and transformation to storage, serving, and observability. Drive hands-on technical contribution through architecture design, code reviews, and complex troubleshooting, setting the technical bar for your team. Set and enforce best practices across data modeling, pipeline reliability, testing, data quality, and documentation. Guide architectural decisions for high-throughput, real-time and batch data systems, ensuring they are scalable, maintainable, and cost-efficient. Ensure the team follows secure data handling practices aligned with PCI-DSS, GDPR, and other compliance frameworks applicable to the payments industry. Champion an AI-first engineering culture, setting standards for AI-assisted development, automated data quality testing, and LLM-powered workflows — ensuring your team treats these tools as a default, not an afterthought. Cross-functional Execution Collaborate closely with Product, Analytics, Machine Learning, Finance, and Compliance teams in an agile environment to deliver against a fast-moving roadmap. Bridge the gap between data consumers (analysts, data scientists, product managers) and the engineering team, ensuring data products are reliable, well-documented, and trusted across the organization. Drive the evolution of data infrastructure to support new markets, new payment providers, and growing regulatory requirements. Translate business priorities into engineering goals, managing trade-offs between speed, reliability, and technical debt. Skills You Need Minimum Qualifications Experience managing and growing data or software engineering teams, including hiring, coaching, and performance management. Strong ability to drive technical decision-making and manage competing priorities in a fast-paced environment. Excellent communication skills — able to engage effectively with both technical and non-technical stakeholders. Solid hands-on data or software engineering background: experience designing data pipelines, data models, and platform architecture at scale. Proficiency in Python and/or SQL; comfort navigating across modern data stacks. Deep understanding of streaming and batch processing architectures – Kafka, Spark, Flink, Airflow, or equivalent. Experience with cloud data infrastructure (AWS, GCP, or Azure) and modern data platform tools (e.g., dbt, data lakehouse patterns). Knowledge of data quality, observability, and governance principles. Champion of AI-first development — experience setting standards for AI-assisted workflows, automated testing, and code generation using LLMs and tools like Claude Code or similar. Experience delivering in agile environments, adapting processes to what actually works for the team. Professional proficiency in English — written and spoken. Preferred Qualifications Experience in the payments or fintech industry. Familiarity with real-time analytics, event-driven architectures, and high-volume transactional data. Exposure to ML platform design or feature store infrastructure. Experience with DevOps practices applied to data: CI/CD for pipelines, infrastructure as code, and data contracts. What We Offer at Yuno Competitive Compensation. Remote Work – You can work from everywhere! Home Office Bonus – A one-time allowance to help you create your ideal home office. Work Equipment. Stock Options. Health Plan wherever you are. Flexible Days Off. Language, Professional, and Personal Growth courses. Remote, Europe · Full Time · Experienced Engineering Manager · +6 Years of Experience Who We Are At Yuno, we are building the payment infrastructure that allows all companies to participate in the global market. Founded by seasoned experts from the payments and tech industries — including the team behind Rappi, one of Latin America's most ambitious tech companies — our technology provides access to leading payment capabilities, enabling companies to engage customers confidently and maintain global operations through seamless integrations. We empower high-performing teams at brands like InDrive, McDonald's, Rappi, and Viva Aerobus to connect to 300+ payment methods worldwide via a single API. By leveraging advanced AI and the latest technologies, we orchestrate smart routing and fraud prevention across 80+ countries. About The Role We are orchestrating a high-performing data team that works with pace and enthusiasm! Yuno moves money across borders for companies that can't afford for payments to fail. Our data platform is what makes that visible — to our product teams, our clients, and ourselves. As an Engineering Manager within the Data team, you will lead a team of data engineers responsible for the platform that processes billions of payment events across 80+ countries. You will own both the people strategy and set technical direction for your team that sits at the core of Yuno's business: enabling fraud detection, revenue analytics, payment optimization, and data-driven product decisions. You will operate in a fast-moving, global environment where data is mission-critical. Your Contribution Will Be Team Leadership Lead and develop a multidisciplinary data engineering team, fostering a culture of technical excellence, ownership, and continuous improvement. Mentor engineers at all levels — supporting their growth through coaching, structured feedback, and clear career expectations. Drive hiring processes to attract and retain top data engineering talent globally. Create an environment where engineers are empowered to take ownership and deliver with autonomy and pace. Technical Ownership Own the full lifecycle for your team — from ingestion and transformation to storage, serving, and observability. Drive hands-on technical contribution through architecture design, code reviews, and complex troubleshooting, setting the technical bar for your team. Set and enforce best practices across data modeling, pipeline reliability, testing, data quality, and documentation. Guide architectural decisions for high-throughput, real-time and batch data systems, ensuring they are scalable, maintainable, and cost-efficient. Ensure the team follows secure data handling practices aligned with PCI-DSS, GDPR, and other compliance frameworks applicable to the payments industry. Champion an AI-first engineering culture, setting standards for AI-assisted development, automated data quality testing, and LLM-powered workflows — ensuring your team treats these tools as a default, not an afterthought. Cross-functional Execution Collaborate closely with Product, Analytics, Machine Learning, Finance, and Compliance teams in an agile environment to deliver against a fast-moving roadmap. Bridge the gap between data consumers (analysts, data scientists, product managers) and the engineering team, ensuring data products are reliable, well-documented, and trusted across the organization. Drive the evolution of data infrastructure to support new markets, new payment providers, and growing regulatory requirements. Translate business priorities into engineering goals, managing trade-offs between speed, reliability, and technical debt. Skills You Need Minimum Qualifications Experience managing and growing data or software engineering teams, including hiring, coaching, and performance management. Strong ability to drive technical decision-making and manage competing priorities in a fast-paced environment. Excellent communication skills — able to engage effectively with both technical and non-technical stakeholders. Solid hands-on data or software engineering background: experience designing data pipelines, data models, and platform architecture at scale. Proficiency in Python and/or SQL; comfort navigating across modern data stacks. Deep understanding of streaming and batch processing architectures – Kafka, Spark, Flink, Airflow, or equivalent. Experience with cloud data infrastructure (AWS, GCP, or Azure) and modern data platform tools (e.g., dbt, data lakehouse patterns). Knowledge of data quality, observability, and governance principles. Champion of AI-first development — experience setting standards for AI-assisted workflows, automated testing, and code generation using LLMs and tools like Claude Code or similar. Experience delivering in agile environments, adapting processes to what actually works for the team. Professional proficiency in English — written and spoken. Preferred Qualifications Experience in the payments or fintech industry. Familiarity with real-time analytics, event-driven architectures, and high-volume transactional data. Exposure to ML platform design or feature store infrastructure. Experience with DevOps practices applied to data: CI/CD for pipelines, infrastructure as code, and data contracts. What We Offer at Yuno Competitive Compensation. Remote Work – You can work from everywhere! Home Office Bonus – A one-time allowance to help you create your ideal home office. Work Equipment. Stock Options. Health Plan wherever you are. Flexible Days Off. Language, Professional, and Personal Growth courses. **Live in Yuno’s hiring system.** Read from the company's own applicant tracking system, not reposted from a job board — so it's a real, open requisition rather than an ad that outlived the role. 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Founded by seasoned experts from the payments and tech industries \u2014 including the team behind Rappi, one of Latin America\u0026#39;s most ambitious tech companies \u2014 our technology provides access to leading payment capabilities, enabling companies to engage customers confidently and maintain global operations through seamless integrations.\u003Cbr /\u003EWe empower high-performing teams at brands like InDrive, McDonald\u0026#39;s, Rappi, and Viva Aerobus to connect to 300\u002B payment methods worldwide via a single API. By leveraging advanced AI and the latest technologies, we orchestrate smart routing and fraud prevention across 80\u002B countries.\u003C/p\u003E\u003Cp\u003EAbout The Role\u003Cbr /\u003EWe\u0026#160;are orchestrating a high-performing data team that works with pace and enthusiasm!\u003Cbr /\u003EYuno moves money across borders for companies that can\u0026#39;t afford for payments to fail. Our data platform is what makes that visible \u2014 to our product teams, our clients, and ourselves.\u003Cbr /\u003EAs an Engineering Manager within the Data team, you will lead a team of data engineers responsible for the platform that processes billions of payment events across 80\u002B countries.\u0026#160;\u003Cbr /\u003EYou will own both the people strategy and set technical direction for your team that sits at the core of Yuno\u0026#39;s business: enabling fraud detection, revenue analytics, payment optimization, and data-driven product decisions. You will operate in a fast-moving, global environment where data is mission-critical.\u003C/p\u003E\u003Cp\u003EYour Contribution Will Be\u003Cbr /\u003ETeam Leadership\u003Cbr /\u003ELead and develop a multidisciplinary data engineering team, fostering a culture of technical excellence, ownership, and continuous improvement.\u003Cbr /\u003EMentor engineers at all levels \u2014 supporting their growth through coaching, structured feedback, and clear career expectations.\u003Cbr /\u003EDrive hiring processes to attract and retain top data engineering talent globally.\u003Cbr /\u003ECreate an environment where engineers are empowered to take ownership and deliver with autonomy and pace.\u003Cbr /\u003ETechnical Ownership\u003Cbr /\u003EOwn the full lifecycle for your team \u2014 from ingestion and transformation to storage, serving, and observability.\u003Cbr /\u003EDrive hands-on technical contribution through architecture design, code reviews, and complex troubleshooting, setting the technical bar for your team.\u003Cbr /\u003ESet and enforce best practices across data modeling, pipeline reliability, testing, data quality, and documentation.\u003Cbr /\u003EGuide architectural decisions for high-throughput, real-time and batch data systems, ensuring they are scalable, maintainable, and cost-efficient.\u003Cbr /\u003EEnsure the team follows secure data handling practices aligned with PCI-DSS, GDPR, and other compliance frameworks applicable to the payments industry.\u003Cbr /\u003EChampion an AI-first engineering culture, setting standards for AI-assisted development, automated data quality testing, and LLM-powered workflows \u2014 ensuring your team treats these tools as a default, not an afterthought.\u003Cbr /\u003ECross-functional Execution\u003Cbr /\u003ECollaborate closely with Product, Analytics, Machine Learning, Finance, and Compliance teams in an agile environment to deliver against a fast-moving roadmap.\u003Cbr /\u003EBridge the gap between data consumers (analysts, data scientists, product managers) and the engineering team, ensuring data products are reliable, well-documented, and trusted across the organization.\u003Cbr /\u003EDrive the evolution of data infrastructure to support new markets, new payment providers, and growing regulatory requirements.\u003Cbr /\u003ETranslate business priorities into engineering goals, managing trade-offs between speed, reliability, and technical debt.\u003C/p\u003E\u003Cp\u003ESkills You Need\u003Cbr /\u003EMinimum Qualifications\u003Cbr /\u003EExperience managing and growing data or software engineering teams, including hiring, coaching, and performance management.\u003Cbr /\u003EStrong ability to drive technical decision-making and manage competing priorities in a fast-paced environment.\u003Cbr /\u003EExcellent communication skills \u2014 able to engage effectively with both technical and non-technical stakeholders.\u003Cbr /\u003ESolid hands-on data or software engineering background: experience designing data pipelines, data models, and platform architecture at scale.\u003Cbr /\u003EProficiency in Python and/or SQL; comfort navigating across modern data stacks.\u003Cbr /\u003EDeep understanding of streaming and batch processing architectures \u2013 Kafka, Spark, Flink, Airflow, or equivalent.\u003Cbr /\u003EExperience with cloud data infrastructure (AWS, GCP, or Azure) and modern data platform tools (e.g., dbt, data lakehouse patterns).\u003Cbr /\u003EKnowledge of data quality, observability, and governance principles.\u003Cbr /\u003EChampion of AI-first development \u2014 experience setting standards for AI-assisted workflows, automated testing, and code generation using LLMs and tools like Claude Code or similar.\u003Cbr /\u003EExperience delivering in agile environments, adapting processes to what actually works for the team.\u003Cbr /\u003EProfessional proficiency in English \u2014 written and spoken.\u003Cbr /\u003EPreferred Qualifications\u003Cbr /\u003EExperience in the payments or fintech industry.\u003Cbr /\u003EFamiliarity with real-time analytics, event-driven architectures, and high-volume transactional data.\u003Cbr /\u003EExposure to ML platform design or feature store infrastructure.\u003Cbr /\u003EExperience with DevOps practices applied to data: CI/CD for pipelines, infrastructure as code, and data contracts.\u003C/p\u003E\u003Cp\u003EWhat We Offer at Yuno\u003Cbr /\u003ECompetitive Compensation.\u003Cbr /\u003ERemote Work \u2013 You can work from everywhere!\u003Cbr /\u003EHome Office Bonus \u2013 A one-time allowance to help you create your ideal home office.\u003Cbr /\u003EWork Equipment.\u003Cbr /\u003EStock Options.\u003Cbr /\u003EHealth Plan wherever you are.\u003Cbr /\u003EFlexible Days Off.\u003Cbr /\u003ELanguage, Professional, and Personal Growth courses.\u003C/p\u003E\u003Cp\u003ERemote, Europe\u0026#160; \u0026#183; Full Time \u0026#183; Experienced Engineering Manager \u0026#183; \u002B6 Years of Experience\u003C/p\u003E\u003Cp\u003EWho We Are\u003Cbr /\u003EAt Yuno, we are building the payment infrastructure that allows all companies to participate in the global market. Founded by seasoned experts from the payments and tech industries \u2014 including the team behind Rappi, one of Latin America\u0026#39;s most ambitious tech companies \u2014 our technology provides access to leading payment capabilities, enabling companies to engage customers confidently and maintain global operations through seamless integrations.\u003Cbr /\u003EWe empower high-performing teams at brands like InDrive, McDonald\u0026#39;s, Rappi, and Viva Aerobus to connect to 300\u002B payment methods worldwide via a single API. By leveraging advanced AI and the latest technologies, we orchestrate smart routing and fraud prevention across 80\u002B countries.\u003C/p\u003E\u003Cp\u003EAbout The Role\u003Cbr /\u003EWe\u0026#160;are orchestrating a high-performing data team that works with pace and enthusiasm!\u003Cbr /\u003EYuno moves money across borders for companies that can\u0026#39;t afford for payments to fail. Our data platform is what makes that visible \u2014 to our product teams, our clients, and ourselves.\u003Cbr /\u003EAs an Engineering Manager within the Data team, you will lead a team of data engineers responsible for the platform that processes billions of payment events across 80\u002B countries.\u0026#160;\u003Cbr /\u003EYou will own both the people strategy and set technical direction for your team that sits at the core of Yuno\u0026#39;s business: enabling fraud detection, revenue analytics, payment optimization, and data-driven product decisions. You will operate in a fast-moving, global environment where data is mission-critical.\u003C/p\u003E\u003Cp\u003EYour Contribution Will Be\u003Cbr /\u003ETeam Leadership\u003Cbr /\u003ELead and develop a multidisciplinary data engineering team, fostering a culture of technical excellence, ownership, and continuous improvement.\u003Cbr /\u003EMentor engineers at all levels \u2014 supporting their growth through coaching, structured feedback, and clear career expectations.\u003Cbr /\u003EDrive hiring processes to attract and retain top data engineering talent globally.\u003Cbr /\u003ECreate an environment where engineers are empowered to take ownership and deliver with autonomy and pace.\u003Cbr /\u003ETechnical Ownership\u003Cbr /\u003EOwn the full lifecycle for your team \u2014 from ingestion and transformation to storage, serving, and observability.\u003Cbr /\u003EDrive hands-on technical contribution through architecture design, code reviews, and complex troubleshooting, setting the technical bar for your team.\u003Cbr /\u003ESet and enforce best practices across data modeling, pipeline reliability, testing, data quality, and documentation.\u003Cbr /\u003EGuide architectural decisions for high-throughput, real-time and batch data systems, ensuring they are scalable, maintainable, and cost-efficient.\u003Cbr /\u003EEnsure the team follows secure data handling practices aligned with PCI-DSS, GDPR, and other compliance frameworks applicable to the payments industry.\u003Cbr /\u003EChampion an AI-first engineering culture, setting standards for AI-assisted development, automated data quality testing, and LLM-powered workflows \u2014 ensuring your team treats these tools as a default, not an afterthought.\u003Cbr /\u003ECross-functional Execution\u003Cbr /\u003ECollaborate closely with Product, Analytics, Machine Learning, Finance, and Compliance teams in an agile environment to deliver against a fast-moving roadmap.\u003Cbr /\u003EBridge the gap between data consumers (analysts, data scientists, product managers) and the engineering team, ensuring data products are reliable, well-documented, and trusted across the organization.\u003Cbr /\u003EDrive the evolution of data infrastructure to support new markets, new payment providers, and growing regulatory requirements.\u003Cbr /\u003ETranslate business priorities into engineering goals, managing trade-offs between speed, reliability, and technical debt.\u003C/p\u003E\u003Cp\u003ESkills You Need\u003Cbr /\u003EMinimum Qualifications\u003Cbr /\u003EExperience managing and growing data or software engineering teams, including hiring, coaching, and performance management.\u003Cbr /\u003EStrong ability to drive technical decision-making and manage competing priorities in a fast-paced environment.\u003Cbr /\u003EExcellent communication skills \u2014 able to engage effectively with both technical and non-technical stakeholders.\u003Cbr /\u003ESolid hands-on data or software engineering background: experience designing data pipelines, data models, and platform architecture at scale.\u003Cbr /\u003EProficiency in Python and/or SQL; comfort navigating across modern data stacks.\u003Cbr /\u003EDeep understanding of streaming and batch processing architectures \u2013 Kafka, Spark, Flink, Airflow, or equivalent.\u003Cbr /\u003EExperience with cloud data infrastructure (AWS, GCP, or Azure) and modern data platform tools (e.g., dbt, data lakehouse patterns).\u003Cbr /\u003EKnowledge of data quality, observability, and governance principles.\u003Cbr /\u003EChampion of AI-first development \u2014 experience setting standards for AI-assisted workflows, automated testing, and code generation using LLMs and tools like Claude Code or similar.\u003Cbr /\u003EExperience delivering in agile environments, adapting processes to what actually works for the team.\u003Cbr /\u003EProfessional proficiency in English \u2014 written and spoken.\u003Cbr /\u003EPreferred Qualifications\u003Cbr /\u003EExperience in the payments or fintech industry.\u003Cbr /\u003EFamiliarity with real-time analytics, event-driven architectures, and high-volume transactional data.\u003Cbr /\u003EExposure to ML platform design or feature store infrastructure.\u003Cbr /\u003EExperience with DevOps practices applied to data: CI/CD for pipelines, infrastructure as code, and data contracts.\u003C/p\u003E\u003Cp\u003EWhat We Offer at Yuno\u003Cbr /\u003ECompetitive Compensation.\u003Cbr /\u003ERemote Work \u2013 You can work from everywhere!\u003Cbr /\u003EHome Office Bonus \u2013 A one-time allowance to help you create your ideal home office.\u003Cbr /\u003EWork Equipment.\u003Cbr /\u003EStock Options.\u003Cbr /\u003EHealth Plan wherever you are.\u003Cbr /\u003EFlexible Days Off.\u003Cbr /\u003ELanguage, Professional, and Personal Growth courses.\u003C/p\u003E","identifier":{"@type":"PropertyValue","name":"Gurify","value":"engineering-manager-data-platform-at-yuno-44abcce51f7b"},"url":"https://gurify.com/job/engineering-manager-data-platform-at-yuno-44abcce51f7b","datePosted":"2026-04-24","validThrough":"2026-11-04T23:59:59Z","hiringOrganization":{"@type":"Organization","name":"Yuno","sameAs":"https://jobs.lever.co/yuno"},"directApply":false,"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressCountry":"GB","addressLocality":"London"}},"employmentType":"FULL_TIME"} ``` ```json {"@context":"https://schema.org/","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Jobs","item":"https://gurify.com/jobs"},{"@type":"ListItem","position":2,"name":"United Kingdom","item":"https://gurify.com/jobs/united-kingdom"},{"@type":"ListItem","position":3,"name":"Engineering Manager \u2013 Data Platform","item":"https://gurify.com/job/engineering-manager-data-platform-at-yuno-44abcce51f7b"}]} ```