Nubank Staff Software Engineer at Nubank working on scalable distributed systems and ML-enabled solutions. Responsible for designing data pipelines, deploying ML models, and building microservices.
Responsibilities
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.
Qualification
Understanding of ML model lifecycle
Required
Deep programming experience in one or more general-purpose languages (e.g. Python, Clojure, Scala, Java), with a track record of guiding technical decisions and raising engineering standards
Experience designing analytical data environments and data engineering solutions: pipelines, ETL/ELT, and data modeling
Understanding of ML model lifecycle, from training and evaluation to deployment and monitoring
Experience guiding the technical design of distributed systems, microservices and asynchronous architectures
Strong communication skills to influence and align both technical and business stakeholders
Passion for building and leading the delivery of high-quality software and data products
Preferred
Experience with cloud platforms such as AWS, GCP or Azure
Knowledge of data architecture patterns (Data Lake, Data Warehouse, Data Mart)
Familiarity with ML frameworks and feature engineering pipelines
Experience with data visualization tools (Looker, Power BI, Tableau or similar)
Knowledge of software engineering best practices: testing, clean code, documentation
