At a Glance
- Tasks: Lead the design and implementation of scalable data pipelines for payment transactions.
- Company: Yuno, a cutting-edge payment infrastructure company with a global impact.
- Benefits: Competitive salary, remote work, stock options, and home office support.
- Other info: Mentorship opportunities and a culture of AI-first engineering.
- Why this job: Join a dynamic team solving complex data challenges in the fintech space.
- Qualifications: 8+ years in data engineering with expertise in large-scale data platforms.
The predicted salary is between 80000 - 100000 £ per year.
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.
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.
If you are a Staff Engineer with passion and drive who enjoys solving complex data problems and driving engineering standards and initiatives end-to-end, then we are looking for you. You will play a pivotal role within the Data team that powers Yuno and its payment platform, while helping co-design and implement an architecture that enables the entire organization to operate on reliable, fast, and trustworthy data.
Your Contribution Will Be
- The stack is modern: StarRocks as our primary analytical layer, Flink for processing, DBT for transformation, Airflow for orchestration and various tooling for surfacing insights.
- The hard work of making it super reliable is still in front of us — and that's exactly why this role exists.
Technical Leadership
- Define architecture within the data platform, structure and deliver projects and initiatives end-to-end.
- Act as a technical reference point for the Data team, setting quality standards, testing, observability, data modeling, and documentation.
- Lead the design and implementation of scalable, low-latency data pipelines that process high-volume payment transactions in real time.
- Champion an AI-first engineering culture, establishing standards for AI-assisted development, automated data quality testing, and LLM-powered data workflows.
Hands-On Engineering
- Design and build data pipelines for large volumes of payment data that are performant, reliable, and correct — not just fast.
- Design scalable data models that support business-critical use cases: fraud detection, revenue analytics, payment success rate optimization, regulatory reporting.
- Own platform reliability — SLAs, data quality, alerting, and incident response for data services.
- Ensure secure data handling practices aligned with PCI-DSS, GDPR, and other compliance frameworks relevant to the payments industry.
Cross-Functional Impact
- Partner with Product, AI, and Finance teams to translate business needs into scalable data solutions.
- Contribute to the roadmap of the data platform and proactively identify opportunities to unlock new business value through data.
- Mentor senior and mid-level engineers, raising the technical bar across the team through code reviews, design reviews, and knowledge-sharing sessions.
- Collaborate with Data Consumers (analysts, data scientists, product managers) to ensure data products are reliable, well-documented, and fit for purpose.
Minimum Qualifications
- 8+ years of experience in data engineering, software engineering, or a related field, with at least 2 years operating at a staff or principal level.
- Deep expertise in designing and building large-scale data platforms — streaming, batch, or hybrid architectures.
- Hands-on experience with Spark, Flink, Kafka, StarRocks, or equivalent.
- Strong Python and SQL skills; comfort working across multiple languages and paradigms.
- Solid understanding of data modeling techniques: dimensional modeling, Data Vault, or lakehouse patterns.
- Experience with cloud data infrastructure (AWS, GCP, or Azure), including managed services for storage, compute, and orchestration.
- Strong grasp of data quality, observability, and governance principles.
- Proven ability to set standards and lead technical initiatives across multiple teams without direct authority.
- Professional proficiency in English — written and spoken.
Preferred Qualifications
- Experience in the payments or fintech industry.
- Familiarity with dbt, Great Expectations, or similar.
- Experience with event-driven services and data mesh approaches.
- Exposure to ML platform design or feature store infrastructure.
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.
Staff Data Platform Engineer - Remote + Equity employer: Yuno
At Yuno, we pride ourselves on being an exceptional employer that champions innovation and collaboration in the fintech space. Our remote work culture allows for flexibility and a healthy work-life balance, while our commitment to employee growth is evident through various professional development courses and mentorship opportunities. With competitive compensation, stock options, and a focus on building a diverse and inclusive team, Yuno is the ideal place for passionate engineers looking to make a meaningful impact in the world of payments.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Data Platform Engineer - Remote + Equity
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with online communities. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for those interviews by practising common questions and showcasing your technical skills. Use platforms like StudySmarter to brush up on your knowledge and get comfortable discussing your past projects and experiences.
✨Tip Number 3
Don’t just apply blindly! Tailor your approach for each company. Research Yuno’s values and tech stack, and be ready to discuss how your experience aligns with their needs during interviews.
✨Tip Number 4
Finally, apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the Yuno team.
We think you need these skills to ace Staff Data Platform Engineer - Remote + Equity
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Staff Data Platform Engineer role. Highlight your expertise in data engineering, especially with tools like Spark and Flink, to catch our eye!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about data engineering and how you can contribute to Yuno's mission. Share specific examples of past projects that showcase your problem-solving skills and technical leadership.
Showcase Your Technical Skills:Don’t just list your skills; demonstrate them! Include links to any relevant projects or GitHub repositories where we can see your work in action. This helps us understand your hands-on experience and coding style.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right team!
How to prepare for a job interview at Yuno
✨Know Your Tech Stack
Familiarise yourself with the technologies mentioned in the job description, like StarRocks, Flink, and DBT. Be ready to discuss your hands-on experience with these tools and how you've used them to solve complex data problems.
✨Showcase Your Leadership Skills
As a Staff Engineer, you'll need to demonstrate your ability to lead technical initiatives. Prepare examples of how you've set quality standards or mentored other engineers in previous roles. This will show that you can elevate the team's performance.
✨Understand Business Impact
Yuno is all about enabling businesses to thrive through reliable payment solutions. Be prepared to discuss how your work in data engineering has directly contributed to business outcomes, such as fraud detection or revenue analytics.
✨Prepare for Cross-Functional Collaboration
You'll be working closely with various teams, so think of examples where you've successfully partnered with product managers, analysts, or finance teams. Highlight your communication skills and how you translate technical needs into business solutions.
