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About the Role

We are seeking an experienced software engineer to enhance and manage Nubank’s messaging platform and its large-scale asynchronous communication infrastructure. This role involves critical platform capabilities supporting diverse internal systems across multiple business domains and countries. The platform operates in a complex environment with extensive clusters, brokers, and topics, handling significant daily data volumes across various AWS accounts. Lead engineers are expected to independently tackle technical challenges, improve system reliability and operability, and influence engineering decisions in collaboration with the team. While Kafka experience is beneficial, it is not mandatory. A strong understanding of distributed systems infrastructure, particularly Kubernetes, networking, and AWS, is essential.

Responsibilities

Operate and improve large-scale messaging and platform infrastructure based on Kafka used by critical systems across Nubank
Contribute to the reliability, scalability, and performance of asynchronous communication platforms
Help design and implement solutions for high-throughput, low-latency, and fault-tolerant systems
Improve observability, automation, and operational excellence across the platform
Support incident analysis, troubleshooting, and root cause remediation in production environments
Optimize infrastructure usage and help drive efficiency and cost awareness across AWS-based environments
Work on platform capabilities that enable safe growth in message volume, topic count, and cluster footprint
Partner with other engineers and teams to evolve platform standards, tooling, and best practices
Contribute to architectural discussions involving messaging, traffic patterns, service communication, and platform reliability

Requirements

Strong software engineering fundamentals and experience working with distributed systems in production.
Solid experience with Kubernetes, networking, and AWS in large-scale or business-critical environments.
Experience operating infrastructure-heavy platforms with high reliability and availability requirements.
Ability to troubleshoot complex production issues across application, infrastructure, and network layers.
Experience improving observability, automation, and operational tooling.
Good understanding of scalability, resilience, performance, and failure isolation patterns.
Ability to work autonomously on ambiguous technical problems and drive them to execution.
Strong collaboration skills and ability to work across team boundaries.

Skills

Kubernetes
Networking
AWS
Distributed systems
Messaging technologies
Streaming technologies
Platform engineering
SRE
Infrastructure-focused backend engineering
Multi-account AWS environments
Large-scale cloud operations
High-throughput event-driven architectures
Apache Kafka

Location

Brazil
Mexico
Colombia

Work Type

Full-time

Experience Level

Lead

Salary/Compensations

$210,000 - $252,000

Benefits

Health Insurance
Life Insurance
Pension Plan
Extended maternity and paternity leaves
Nucleo - Our learning platform of courses
NuLanguage - Our language learning program
NuCare - Our mental health and wellness assistance program
Vacations
RSUs

About the Company

Nu is the leading digital bank in Latin America, serving 135 million customers across Brazil, Mexico, and Colombia.
The company has been leading an industry transformation by leveraging data and proprietary technology to develop innovative products and services.
Guided by its mission to fight complexity and empower people, Nu caters to customers’ complete financial journey, promoting financial access and advancement with responsible lending and transparency.
The company is powered by an efficient and scalable business model that combines low cost to serve with growing returns.
Nu’s impact has been recognized in multiple awards, including Time 100 Most Influential Companies, Fast Company’s Most Innovative Companies, and Forbes World’s Best Banks.

Equal Opportunity

Our recruitment process may involve the use of artificial intelligence–enabled tools, such as automated interview transcription and analysis, to support the evaluation process. Artificial intelligence is not used to make final hiring decisions; all decisions are made by human reviewers.