At a Glance
- Tasks: Lead a dynamic data engineering team and drive innovative payment solutions.
- Company: Join Yuno, a cutting-edge payment infrastructure company transforming global transactions.
- Benefits: Enjoy remote work, competitive pay, stock options, and professional development opportunities.
- Other info: Flexible work environment with excellent growth potential and a focus on AI-driven development.
- Why this job: Make a real impact in the fintech space while working with advanced technologies.
- Qualifications: Proven experience in managing data teams and strong technical skills in data engineering.
The predicted salary is between 80000 - 100000 £ per year.
Who We Are
At Yuno, we are building the payment infrastructure that allows all companies to participate in the global market. 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.
- 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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed or wish to exercise your data protection rights, please contact us at hiring@y.uno.
Engineering Manager – Data Platform employer: Yuno
Contact Detail:
Yuno Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Engineering Manager – Data Platform
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend virtual meetups, and engage with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by researching the company and its culture. Understand their products and services, especially how they relate to data engineering. This will help you tailor your responses and show that you're genuinely interested in joining their team.
✨Tip Number 3
Practice your technical skills! Brush up on your Python, SQL, and any relevant data tools. Consider doing mock interviews with friends or using platforms that simulate technical interviews to get comfortable with the process.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Engineering Manager – Data Platform
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Engineering Manager role. Highlight your experience in managing data engineering teams and any relevant projects that showcase your technical skills. We want to see how you fit into our mission!
Showcase Your Leadership Skills: As an Engineering Manager, your leadership style is crucial. Share examples of how you've mentored engineers and fostered a culture of excellence in your previous roles. We love seeing candidates who can inspire and empower their teams!
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language and avoid jargon where possible. We appreciate candidates who can communicate effectively with both technical and non-technical stakeholders.
Apply Through Our Website: We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Yuno
✨Know Your Data Inside Out
Make sure you’re well-versed in the data technologies mentioned in the job description, like Python, SQL, and cloud platforms. Brush up on your knowledge of streaming and batch processing architectures, as well as data pipeline design. Being able to discuss these topics confidently will show that you're ready to lead a high-performing data team.
✨Showcase Your Leadership Skills
Prepare examples of how you've successfully managed and developed engineering teams in the past. Think about specific instances where you mentored engineers or drove hiring processes. Highlighting your ability to foster a culture of technical excellence and ownership will resonate well with the interviewers.
✨Communicate Effectively
Since the role involves collaborating with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. Be ready to discuss how you bridge gaps between data consumers and engineering teams. Good communication can set you apart from other candidates.
✨Embrace the AI Culture
Given the emphasis on an AI-first engineering culture, be prepared to discuss your experience with AI-assisted development and automated testing. Share any relevant projects where you’ve implemented these practices, as this will demonstrate your alignment with Yuno's vision and your readiness to champion innovative solutions.