Data Automation & Efficiency Sr. Specialist - Internal Controls SOX

Nubank
Brazil, Sao PauloPosted 26 March 2026

Job Description

About Us Nu is one of the largest digital financial platforms in the world, with more than 122 million customers across Brazil, Mexico, and Colombia. Guided by our mission to fight complexity and empower people, we are redefining financial services in Latin America and this is still just the beginning of the purple future we're building. Listed on the New York Stock Exchange (NYSE: NU), we combine proprietary technology, data intelligence, and an efficient operating model to deliver financial products that are simple, accessible, and human. Our impact has been recognized by global rankings such as Time 100 Companies, Fast Company’s Most Innovative Companies, and Forbes World’s Best Bank. Visit our institutional page https://international.nubank.com.br/careers/ About the Team The Internal Controls SOX squad is responsible for assessing risks and testing internal controls over financial reporting across Nubank. This role will deepen our efficiency and analytics capabilities using data, automation, and AI to scale our SOX program and operational routines. You will act as a focal point to: leading complex initiatives with limited oversight, shaping how we use data/AI to run SOX more efficiently, and coaching the team on best practices in analytics and process improvement. You will be responsible for Proactively identify opportunities for process and efficiency improvements in SOX planning, testing, and reporting, using data analysis, AI and analytics tools. Design, implement, and iterate metrics and KPIs (e.g., productivity, timeliness, quality, coverage) to monitor SOX deliverables and drive decisions. Build and maintain dashboards that provide actionable insights for ICFR stakeholders (SOX team, Finance, Product BCOs, Risk, and leadership). Use SQL and other programming languages (e.g., Python ) to extract, transform, and analyze large, complex datasets from multiple sources. Experiment with and operationalize AI solutions (e.g., LLMs, code assistants, automation scripts) to streamline testing, documentation, and evidence management. Obtain a solid understanding of business and IT processes (products, accounting flows, operational controls) and translate operational analysis and quality‑assurance metrics into data‑driven solutions that boost efficiency and significantly reduce manual workload for the team . Partner with engineers and data teams to improve data quality, lineage, and monitoring for SOX solutions. Coach and support other team members on data, automation, and visualization best practices, raising the analytics bar of the chapter . What we’re looking for Solid experience in data/analytics roles (e.g., Data/Business/Finance/Risk Analyst) with increasing scope and complexity; Strong hands‑on skills in SQL and at least one programming language (e.g. Python ) applied to large datasets. Ability to create high-quality documentation (mapping the transition from AS-IS to TO-BE) that effectively communicates with cross-functional teams. Comfortable integrating with corporate systems frequently used in projects, such as SAP, Databricks, Jira, Slack, Google Workspace, and AWS (Lambda/S3). Proven track record building dashboards and reports in modern BI tools (e.g., Looker, Tableau, Power BI or similar), from requirements to production. Demonstrated experience designing and tracking metrics, SLAs and KPIs to manage operational or risk/controls processes. Experience applying AI or advanced analytics (e.g., LLMs, automation, statistical analysis, anomaly detection) to improve efficiency or quality in business processes. Ability to lead end‑to‑end projects with limited oversight, coordinating multiple stakeholders and communicating clearly with technical and non‑technical audiences. Strong written and verbal communication in English ; Spanish is a plus. Nice to have Prior experience in SOX, internal audit, risk management, or financial controls teams. Experience work ... (truncated, view full listing at source)
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