Business Analysts are fundamental in the decision process because they must not only be able to deal with large amounts of information and data, but also always think of ways to improve our clients' experience. It is BA's responsibility to structure the data, analyze it and use the results to test different solutions with the aim of improving Nubank's efficiency.
Responsibilities
Do investigative work focused on deciding which data makes the most sense to use in which situation
Support team in making data-based decisions by monitoring analysis and decisions
Learning how to work with a large volume of data to build a solid foundation for decision making with calculated risks
Associate level Software Engineer to work across a broad range of applications and extremely diverse set of technologies to keep the platform operating at peak efficiency.
Responsibilities
Performance tune applications to improve memory and CPU utilization
Facilitate robust utilization of the firm's application and data platform capabilities by the different functional domains as a SME
Utilize web development technologies to facilitate application development for front end UI used for firm wide usecases
Develop software for applications that interact with databases like Snowflake, Sybase IQ and distributed HDFS systems
Interact with business and engineering users to help resolve issues with applications
Data Engineering Intern to join the product and delivery team, focusing on building real code, real pipelines, and contributing to features and integrations that run in enterprise production environments, including agentic workflows.
Responsibilities
Help onboard enterprise customer workloads to NexusOne, including data ingestion, transformation, analytics, and AI ops
Build and test product features with a focus on performance, quality, and scale
Contribute to agentic data workflows: pipelines and integrations that let AI agents act on enterprise data
Work hands-on with modern data technologies including Kubernetes, Apache Spark, dbt, Trino, Airflow, and Iceberg
Write Python, Java, or Scala to implement features and modernize customer workloads
Requirements
Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field
Master’s degree in Computer Science, Engineering, Data Science, or a related field
Design, build, and optimize ML models and solutions — spanning traditional statistical ML, neural networks, and deep learning — to solve real-world problems in large-scale, real-time digital performance analytics.
Compensation
The expected salary range for this full-time position is $180,000 - $230,000 + equity + benefits.
Responsibilities
Design, build, and optimize ML models and solutions
Develop innovative approaches for predictive modeling, anomaly detection, and automated alerting
Apply the full algorithm spectrum from classical methods to advanced deep learning architectures
Support AI initiatives including designing AI-driven alerts and contributing to AI roadmaps
Develop POC code and implement ML solutions using AI coding tools
Requirements
PhD in Computer Science, Statistics, or related field
MS with 3+ years of applied ML/data science experience
Nice to have: Real-time data processing and streaming analytics
Support the Data Hub Chapter of an enterprise client, responsible for the analysis, design, implementation, testing and maintenance of Data Warehouse and Data Platform solutions, focusing on data ingestion, integration, transformation and quality.
Responsibilities
Analyze, plan, implement and technically test Data Warehouse solutions and data platform initiatives
Develop and maintain raw data ingestion pipelines for Data Lake and related environments
Ensure data accessibility, referencing, governance and quality across enterprise platforms
Design and implement ETL processes and data integration solutions
Collaborate with Business Areas and Functional Teams to gather requirements and define technical solutions
Requirements
Bachelor's or Master's Degree in Computer Engineering, Information Technology or a related field
Nice to have: Consumer Credit experience in Banking environments
Collect, store, process and analyze large datasets to build and implement extract, transfer, load (ETL) processes, leading migration of data pipelines from Synapse to Databricks.
Compensation
$50-53/Hour on W2/C2C (All Inclusive)
Responsibilities
Lead migration of data pipelines from Synapse to Databricks
Architect and implement batch + real-time data pipelines using PySpark, Databricks, and Event Hubs
Establish data engineering best practices and mentor junior engineers
Drive CI/CD automation with AzDO and Git
Ensure data quality, governance, and compliance (Collibra)
Requirements
Nice to have: Collibra
Nice to have: Azure/Databricks certifications
Nice to have: Azure functions using Python/Node.js
Conception et implémentation de systèmes data-intensive et de pipelines de récupération, de traitement et de stockage de la donnée. Développement de dashboards de datavisualisation et d’aide à la décision. Travaux d’intégration sur des plateformes BigData/IA. Modélisation de la donnée.
Responsibilities
Conception et implémentation de systèmes data-intensive et de pipelines de récupération, de traitement et de stockage de la donnée
Développement de dashboards de datavisualisation et d’aide à la décision
Travaux d’intégration sur des plateformes BigData/IA
Modélisation de la donnée
Requirements
Bac+5 en informatique (École d'ingénieur ou Master)
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