Staff Analytics Engineer

About Us

Nu is one of the largest digital financial platforms in the world, with more than 135 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.

About the Role

Analytics Engineers at Nubank are the bridge between business needs and the data platform — making data available across the entire company through sound modeling, governance, and engineering excellence.

We are looking for a Staff Analytics Engineer (IC7) to lead one of our most strategic data initiatives: building the authoritative, canonical data ecosystem for all money movements across Nubank's global Payments and Transfers Platform. Our mission is to deploy and harden a single source of truth for this critical domain to eliminate fragmented, non-standardized datasets, creating reconciliation failures, regulatory risk, and compounding limitations for AI-powered products.

This is not a migration or maintenance project. You will reimagine the data architecture from first principles — designing what the next generation of financial data infrastructure should look like, then driving its execution across a complex, multi-stakeholder environment. The work will directly fuel Nubank's core products, regulatory operations, and AI roadmap.

This role offers extraordinary visibility: you will lead strategic planning and prioritization on a global scale, and influence the data direction of the organization's central nervous system, and set the technical bar for the entire Analytics Engineering function within Global Core Banking.

What You'll Own

• Canonical Data Strategy: Define and own the vision and roadmap for a canonical data ecosystem covering all payment and transfer flows across products, customers, and borders at Nubank.
• End-to-End Technical Leadership: Lead end-to-end, high-stakes data projects with full autonomy — from requirements gathering and architecture design through delivery, monitoring, and continuous improvement.
• Data Architecture & Engineering: Design and implement robust, scalable data pipelines and models built to last — with an architecture that explicitly supports regulatory, accounting, analytics, and AI use cases.
• Governance & Risk Management: Build and enforce data controls, reconciliation frameworks, and governance standards that reduce regulatory and operational risk across the organization.
• Cross-Functional Influence: Navigate a complex landscape of technical and business stakeholders — aligning teams on standards, negotiating trade-offs, and driving adoption of canonical data sources even when it requires challenging the status quo.
• Agentic AI Integration: Define the AI strategy for your domain — deciding which workflows become AI-native, building reusable AI components, and setting guardrails for regulated financial data flows.
• Technical Leadership & Mentorship: Set the technical bar for the Analytics Engineering function, mentoring ICs up to IC6, contributing to hiring, and shaping how the team grows and operates.
• Strategic Partnership: Partner with data platform, engineering, product, compliance, and finance teams to ensure the ecosystem supports Nubank's most critical business and regulatory requirements.

What We're Looking For

Must-haves

• Proven ownership mindset: Track record of independently leading complex, high-impact data initiatives at scale — not just executing tasks, but owning and driving the entire problem.
• Data architecture expertise: Deep experience designing data architectures for complex domains, including transactional, analytical, and regulatory data models.
• Regulatory environment experience: Experience working in or alongside regulated environments (financial services, fintech, or similar) — understanding of controls, reconciliation, data lineage, and compliance implications.
• Stakeholder management and influence: Demonstrated ability to align diverse stakeholders, influence technical direction across teams, and drive adoption of standards — including the confidence to push back when necessary.
• Technical depth: Advanced SQL and strong proficiency in general-purpose languages (Python, Scala, or similar), with hands-on experience building and maintaining production data pipelines.
• Breadth across the data stack: Cross-tool experience across modern data stacks: streaming platforms, data contracts, data warehouses, and orchestration frameworks.
• Business-to-data translation: Ability to translate ambiguous, complex business challenges into concrete data products and architectural decisions.

Nice to Have

• Experience with AI/ML integration in data workflows, or defining AI-native data strategies.
• Background in financial data modeling (payments, transfers, credit, or accounting data).
• Familiarity with data governance tooling, metadata management, and PII classification.
• Experience mentoring senior engineers and contributing to function-level hiring or capability building.
• Knowledge of software engineering best practices (testing, CI/CD, documentation, clean code).

Why This Role

• Maximum impact & visibility: Highest-visibility data role in core banking — you will work on the central nervous system of all money movements at Nubank, with access to strategic rooms not typically available to ICs.
• Build from scratch: This is a greenfield architecture initiative, not a legacy migration. You will design what the next generation of financial data infrastructure should look like — from scratch.
• Frontier of agentic AI in financial services: The ecosystem you build is the foundation for AI-powered banking. You will define which workflows become AI-native and set the guardrails for agentic financial data flows.
• Cross-border, cross-product scope: Your work will affect products, customers, and operations across multiple countries from day one.
• Outsized ownership for your level: At Staff in this domain, you are effectively the head of data for core banking — with disproportionate influence and ownership relative to your level.

Role Location

Hybrid 2-3 times/week in our office locations in the US: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/