About the job
About Us
Nu is a pioneering leader in the realm of digital financial services, serving over 127 million customers across Brazil, Mexico, and Colombia. We are on a mission to simplify finance and empower individuals, redefining the landscape of financial services in Latin America. With a vision for a vibrant future, our journey is just beginning.
As a publicly traded company on the New York Stock Exchange (NYSE: NU), we leverage cutting-edge technology, data-driven insights, and a streamlined operational model to create financial products that are accessible, straightforward, and user-centric.
Our efforts have garnered recognition from esteemed global rankings, including Time 100 Companies, Fast Company’s Most Innovative Companies, and Forbes World’s Best Bank. To learn more about us, visit our institutional page https://international.nubank.com.br/careers/.
About the Role
At Nubank, safeguarding customer data is crucial to our relationship with more than 100 million users. As a Senior Data Security Engineer, you will play a pivotal role in designing and enhancing the secure infrastructure that empowers our teams to innovate while upholding the highest standards of privacy and compliance. You will lead the collaboration between Data Engineering and Security, ensuring that sensitive data is classified, governed, and monitored throughout our global analytics ecosystem. Your mission will be to strike a balance between risk mitigation and optimal usability and performance, embedding data security into every analytical layer by design.
Key Responsibilities
- Designing Secure Data Architectures: Independently create and enhance secure data ingestion, transformation, and analytics pipelines that handle sensitive and regulated information across all analytics environments.
- Implementing Platform-Level Security: Spearhead the implementation of improvements such as classification tags, policy-driven access controls, and automated validations to minimize risk while ensuring system efficiency.
- Governing Data Models: Oversee the design and evolution of data models and semantic views that inherently enforce security and privacy standards.
- Operationalizing Metadata and Lineage: Lead initiatives to monitor data lineage and sensitivity metadata across essential sources, facilitating scalable governance and observability.
- Executing Audits and Remediation: Proactively manage access reviews and remediation initiatives, identifying weaknesses in least-privilege enforcement and recommending structural enhancements.
