Staff Software Engineer, Data

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

About the Role

As a Staff Software Engineer (Data) , you will be the technical cornerstone of our data ecosystem. At Nu, we don't just "move data" we build the foundational platforms that empower analysts, ML engineers, and product leaders to make the decisions that drive financial inclusion for millions.

You will own the data infrastructure for your domain, tackling highly complex and ambiguous challenges that span multiple departments. You aren't just a builder; you are a strategist who identifies data gaps before they become bottlenecks and treats data quality as a mission critical product. You will set the technical bar for the entire function, ensuring that downstream trust remains unbreakable as we scale.

Responsibilities

Architect Data Excellence: Design and evolve high scale data platforms, storage solutions, and transformation patterns that serve as the "gold standard" for the organization.

Drive Technical Strategy: Define the long term roadmap for data infrastructure, balancing immediate business needs with a 6–12 month strategic horizon.

Champion Data Contracts: Lead the implementation of robust data contracts and schema evolution practices to ensure reliability across global product teams.

Solve Complex Ambiguity: Troubleshoot and resolve the most challenging technical bottlenecks in our data pipelines, improving system observability and performance at scale.

Empower the Function: Act as a key technical advisor for senior leadership, helping to shape strategic investments in our data stack.

Mentor and Scale: Raise the technical bar by mentoring senior engineers, leading cross functional task forces, and fostering a culture of engineering excellence and data driven decision making.

Operational Leadership: Pioneer architectural patterns that become reference implementations for the entire company.

Qualifications

Required:

Extensive Technical Leadership: Proven experience leading large scale data engineering initiatives in global, high-growth technology environments.

Expertise in Distributed Systems: Deep mastery of data processing frameworks (such as Spark, Flink, or Kafka) and modern cloud data warehousing.

Systems Design Mastery: Ability to independently design and refine solutions for complex data problems, considering long-term scalability and user experience.

Strategic Acumen: Demonstrated ability to link technical decisions to business drivers like operational efficiency and customer acquisition costs.

Proactive Problem Solving: A track record of identifying architectural gaps and implementing fixes independently with high autonomy.

Nice to Have:

Experience with ML Ops and supporting Machine Learning workflows at scale.

Experience in the financial services or FinTech sector.