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Senior Software Engineer

Nubank São PauloEst. Est. BRL 120,000–180,000 / yearSenior

Estimated range based on role, country and industry — not published by the company.

Key requirements

  • Python
  • Java
  • Aws
  • Azure
  • Gcp
  • Machine Learning
  • Tableau
  • Power Bi
  • Looker
About Nu Nu serves more than 140 million customers, guided by a mission to fight complexity and empower people. The company has been leading an industry transformation through innovative products and human-centered services.   Proprietary technology and data at scale power Nu’s digital platform, built to promote financial access, advancement, and transparency. Its business model thrives on customer love and lower costs, feeding a flywheel of growth and profitability. Visit our Institutional Page Engineering at Nubank At Nubank, software engineers sit at the intersection of data, intelligence, and scale. We build systems that process millions of decisions daily, from fraud detection to credit modeling and increasingly, we do this powered by AI. Machine learning is embedded across our core products: in how we assess risk, personalize experiences, and automate decisions at scale. Engineers here don't just consume AI capabilities; they help shape how intelligence is built, deployed, and maintained in production. We do it with engineering rigor, autonomy, and a deep focus on impact. Our engineers work across the full spectrum: designing data pipelines and architectures, deploying and maintaining ML models in production, and building the distributed systems and platforms that power our products. We value small, independent teams that move fast, own their decisions end-to-end, and hold themselves to a high bar for quality and craft. We strive for state-of-the-art software development practices across our entire stack. While we value candidates familiar with our technologies, we're confident that engineers who join Nubank will learn and grow alongside our team: Horizontally scalable microservices written mostly in Clojure, leveraging functional programming and hexagonal architecture High-throughput event-driven architectures for inter-service communication Continuous Integration and Deployment into cloud-native infrastructure Distributed transactional systems built on Datomic, modeling complex business domains with immutable data and strong consistency Modern data platforms built on ETL/ELT best practices, with robust monitoring and observability Our Software Engineers Work with large scale distributed systems Collaborate with building microservices Design, build and maintain robust data pipelines, distributed systems and ML-enabled solutions, ensuring reliability, scalability and performance at scale Deploy and maintain ML models in both batch and real-time scenarios, integrating them with other systems and monitoring through operational and business metrics Lead data and engineering projects end-to-end — from requirements gathering and stakeholder alignment to delivery and iteration Contribute to the design, documentation, maintenance and optimization of our data codebase, platforms and tooling Translate business needs into data products and technical solutions aligned with Nubank's architecture and long-term strategy Partner with technical and business stakeholders to define strategies and deliver high-impact solutions Share knowledge, mentor peers and contribute to engineering and data literacy initiatives across Nubank What We're Looking For Programming experience in one or more general-purpose languages (e.g. Python, Clojure, Scala, Java) Familiarity with analytical data environments and data engineering concepts: pipelines, ETL/ELT, data modeling and storage Understanding of ML model lifecycle, from training and evaluation to deployment and monitoring Familiarity with distributed systems, microservices and asynchronous architectures Strong communication skills to collaborate with both technical and business stakeholders Passion for building high-quality software and data products Nice to Have Experience with cloud platforms such as AWS, GCP or Azure Knowledge of data architecture patterns (Data Lake, Data Warehouse, Data Mart) Familiarity with ML frameworks and

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