Remote Data Engineering Manager — AI-Driven Payments Platform

Remote Data Engineering Manager — AI-Driven Payments Platform

Full-Time 80000 - 100000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Lead a global data engineering team and shape the future of payment technology.
  • Company: Yuno, an innovative AI-driven payments platform with a remote-first culture.
  • Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
  • Other info: Join a fast-paced environment with exciting challenges and career advancement.
  • Why this job: Make a real impact on billions of payment events across 80+ countries.
  • Qualifications: Proven experience in data engineering and strong leadership skills.

The predicted salary is between 80000 - 100000 £ per year.

Yuno is actively seeking an experienced Engineering Manager for the Data team to lead a global data engineering group and shape the platform handling billions of payment events across 80+ countries. You will own people strategy and set the technical direction for your team, driving data pipelines, observability, and data quality to enable fraud detection, revenue analytics, and product decisions in a fast‑moving, remote‑first environment.

Remote Data Engineering Manager — AI-Driven Payments Platform employer: Yuno

Yuno is an exceptional employer that fosters a dynamic and innovative work culture, perfect for those looking to make a significant impact in the payments industry. With a focus on employee growth and development, we offer unique opportunities to engage with high-growth brands across Europe while enjoying the flexibility of remote work and the potential for stock options. Join us to be part of a forward-thinking team that values creativity and collaboration in building cutting-edge payment solutions.

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Contact Details:

Yuno Recruitment Team

We think you need these skills to ace Remote Data Engineering Manager — AI-Driven Payments Platform

Leadership Skills
Data Engineering
Technical Direction
Data Pipelines
Observability
Data Quality
Fraud Detection