United Kingdom
EuropeEngineering Manager – Data Platform
4 мес. назад
United KingdomEuropeSeniorRemote
data engineeringaipayment apifraud detectionrevenue analytics
Lead a team of data engineers responsible for the data platform processing billions of payment events, overseeing people strategy and technical direction at .
О компании
- At , 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.
Обязанности
- We are orchestrating a high-performing data team that works with pace and enthusiasm!
- 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 '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.
Требования
- 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.
Будет плюсом
- 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.
Условия
- 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.
Другое
- Remote, Europe · Full Time · Experienced Engineering Manager · +6 Years of Experience
- 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 — ensuring your team treats these tools as a default, not an afterthought.
- 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.