Engineering Manager – Data Platform
Yuno
Engineering Manager – Data Platform
Yuno is seeking an Engineering Manager for its Data Platform team to lead data engineers processing billions of payment events across 80+ countries. The role requires 6+ years of experience, strong people leadership, hands-on data engineering expertise, and proficiency in Python/SQL, streaming and batch architectures, and cloud data infrastructure.
Engineering Manager – Data Platform
Yuno is seeking an Engineering Manager for its Data Platform team to lead data engineers processing billions of payment events across 80+ countries. The role requires 6+ years of experience, strong people leadership, hands-on data engineering expertise, and proficiency in Python/SQL, streaming and batch architectures, and cloud data infrastructure.
Salary
Core Qualifications
Technical (Must-have)
Soft Skills
Preferred Qualifications
Technical (Nice-to-have)
Key Responsibilities
- 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
- 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
- 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 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