Engineering Manager – Data Platform

Stack

Responsibilities

• ▹Lead and develop a multidisciplinary data engineering team, fostering a culture of technical excellence, ownership and continuous improvement
• ▹Mentor engineers at all levels through coaching, structured feedback and clear career expectations
• ▹Drive hiring processes to attract and retain top data engineering talent globally
• ▹Own the full lifecycle for your team: ingestion, transformation, storage, serving and observability
• ▹Contribute hands-on through architecture design, code reviews and complex troubleshooting
• ▹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
• ▹Ensure secure data handling aligned with PCI-DSS, GDPR and other compliance frameworks in the payments industry
• ▹Champion an AI-first engineering culture: AI-assisted development, automated data quality testing and LLM-powered workflows
• ▹Collaborate with Product, Analytics, Machine Learning, Finance and Compliance teams in an agile environment
• ▹Bridge the gap between data consumers (analysts, data scientists, product managers) and the engineering team
• ▹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

Requirements

• ▹Experience managing and growing data or software engineering teams, including hiring, coaching and performance management
• ▹Ability to drive technical decision-making and manage competing priorities in a fast-paced environment
• ▹Excellent communication skills with technical and non-technical stakeholders
• ▹Solid hands-on data or software engineering background: designing data pipelines, data models and platform architecture at scale
• ▹Proficiency in Python and/or SQL; comfort 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
• ▹AI-first development mindset: experience setting standards for AI-assisted workflows, automated testing and code generation using LLMs and tools like Claude Code
• ▹Experience delivering in agile environments
• ▹Professional proficiency in English, written and spoken
• ▹6+ years of experience

Nice to have

• ▹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
• ▹DevOps practices applied to data: CI/CD for pipelines, infrastructure as code, data contracts

Soft skills

What we offer

• ▹Competitive compensation
• ▹Remote work from anywhere
• ▹One-time home office allowance
• ▹Work equipment
• ▹Stock options
• ▹Health plan wherever you are
• ▹Flexible days off
• ▹Language, professional and personal growth courses

About the company

Yuno builds the payment infrastructure that allows all companies to participate in the global market. It was founded by seasoned payments and tech experts, including the team behind Rappi. Through a single API, brands like InDrive, McDonald's, Rappi and Viva Aerobus connect to 300+ payment methods, with smart routing and fraud prevention across 80+ countries.