资深软件工程师 - 商业智能
Staff Software Engineer - BI Intelligence
Nu是拉丁美洲领先的数字银行,为巴西、墨西哥和哥伦比亚的1.4亿客户提供服务。公司通过利用数据和专有技术,开发创新产品和服务,引领行业变革。
秉承着对抗复杂性、赋能人们的使命,Nu为客户提供完整的金融旅程,通过负责任的贷款和透明度促进金融准入和进步。公司由高效且可扩展的商业模式驱动,结合低成本服务与不断增长的回报。
Nu的影响已获得多项奖项的认可,包括《时代》100家最具影响力公司、《快公司》最具创新力公司以及《福布斯》全球最佳银行。
访问我们的机构页面 https://www.nu.com/2026-en
关于该职位
BI智能团队构建并发展使每位Nu员工能够轻松、安全、大规模且低成本地使用数据的平台。Databricks是我们内部分析生态系统的基础之一,同时还包括支持公司内业务智能、探索和决策的技术。
分析正在经历根本性的转变。我们正从预定义的仪表板和手动编写的查询,转向对话式和代理式体验,让人们可以用自然语言提问,探索关系,创建和验证指标,并更快地从问题转化为洞察。
作为高级软件工程师 – BI智能,您将帮助塑造下一代分析系统。您将在软件工程、SRE、数据平台和应用AI的交叉点上工作,构建可靠且受控的系统,使数据更易访问,同时保护安全性、质量、可追溯性和成本。
您将负责
- 设计和演进服务于Nubankers和公司各业务部门的分析平台。
- 构建基于AI的数据体验,包括自然语言接口、查询生成、工具编排、基础设置和反馈机制。
- 开发可信AI分析所需的基础设施:语义上下文、受控指标、数据契约、血缘关系、质量、访问控制和评估。
- 设计和运营具有强大可观测性、服务目标、安全性、性能和成本控制的可靠分布式系统。
- 推动技术方向,在合作伙伴关系中做出架构决策。
查看英文原文
ABOUT NU
Nu is the leading digital bank in Latin America, serving 140 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.
Visit our Institutional Page https://www.nu.com/2026-en
ABOUT THE ROLE
The BI Intelligence team builds and evolves the platforms that allow every Nubanker to consume data easily, safely, at scale and with lower cost. Databricks is one of the foundations of our internal analytics ecosystem, alongside technologies that support business intelligence, exploration and decision-making across the company.
Analytics is entering a fundamental shift. We are moving beyond predefined dashboards and manually written queries toward conversational and agentic experiences, where people can ask questions in natural language, explore relationships, create and validate metrics, and move from question to insight faster.
As a Staff Software Engineer – BI Intelligence, you will help shape this next generation of analytics. You will work at the intersection of software engineering, SRE, data platforms and applied AI, building reliable and governed systems that make data more accessible while protecting security, quality, traceability and cost.
YOU’LL BE RESPONSIBLE FOR
- Designing and evolving analytics platforms that serve Nubankers and business units across the company.
- Building AI-powered data experiences, including natural-language interfaces, query generation, tool orchestration, grounding and feedback mechanisms.
- Developing the foundations required for trustworthy AI analytics: semantic context, governed metrics, data contracts, lineage, quality, access control and evaluation.
- Designing and operating reliable distributed systems with strong observability, service objectives, security, performance and cost controls.
- Driving technical direction and making architectural decisions in partnership with engineering leadership and cross-functional stakeholders.
- Translating ambiguous problems into clear technical options, trade-offs and execution plans.
- Mentoring engineers and raising the engineering bar through design reviews, pairing, documentation and operational practices.
- Helping turn promising AI capabilities into dependable products that improve how Nubankers work with data.
WHAT WE'RE LOOKING FOR SOMEONE WHO HAS
Required
- Proven experience as a Staff-level Software Engineer or equivalent technical leader delivering high-impact systems in production.
- Strong software engineering fundamentals and an SRE mindset, including experience designing reliable distributed systems, defining service objectives and improving observability.
- Experience with data platforms or analytics infrastructure, such as Databricks, distributed query engines, metadata catalogs, semantic layers or large-scale data systems.
- Deep understanding of data semantics, metric definitions, data contracts, lineage, data quality and access control.
- Experience designing or integrating AI/LLM-powered products, including natural-language interfaces, RAG, tool use, query generation, grounding or evaluation.
- Ability to balance security, governance, reliability, latency, performance and cost at scale.
- Proven ability to lead ambiguous, cross-functional initiatives and drive alignment across teams and stakeholders.
- Strong written and verbal communication skills, including the ability to explain complex technical decisions clearly.
- Experience mentoring engineers and influencing technical direction beyond your immediate team.
Nice to Have
- Experience building conversational analytics, agentic workflows or AI-powered developer/data tools.
- Experience with evaluation frameworks, guardrails and monitoring for AI-generated outputs.
- Background in financial services, fintech or other regulated environments.
WORK SETUP
Location
Brazil
Work model
Hybrid
Office requirement
Hybrid 2–3 times/week: 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/
OUR BENEFITS
- Chance of earning equity at Nubank - [Reminder: Ops Teams don't have equity];
- Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
- Public Transportation Commuting Benefit (Vale-Transporte)
- NuCare – Psychological, Financial and Legal Assistance Program
- Life Insurance
- Medical Plan
- Dental Plan
- NuLanguage – Language Course Program
- Nucleo - Our learning platform of courses
- Extended Parental Leave
- Daycare Allowance
- Parental Consultancy
- Work-from-home Allowance
- Gym Partnerships
- 30 days of paid vacation
- Relocation Assistance Package, if applicable
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.