R&D Team

As part of the Business Lines, R&D teams are responsible for the design and implementation of products. In the context of Data Quality Management, R&D teams are composed of various technical profiles that are involved on Data streams such as:

  • Data Engineers: responsible for building, managing, and optimizing data pipelines and architectures. They work to ensure that data flows seamlessly from source to destination, making it accessible and usable for further analysis. They prepare and transform large volumes of data for analytical or operational uses and are pivotal in implementing the solutions designed by the team.

  • Data Scientists: analyze complex data to extract insights that drive the development of innovative products and solutions. They use statistical modeling, machine learning, and data mining techniques to predict patterns and outcomes from vast datasets. Their work informs product enhancements and strategic decisions, making them integral to the R&D process.

  • Developers: involved in coding and building software applications that process and analyze data streams. Their role focuses on implementing the functional aspects of the products, ensuring they perform optimally and meet the user requirements. They work closely with data engineers and architects to integrate data-driven functionalities into the software products.

  • Data architects: define how data is stored, consumed, integrated, and managed by different data entities and IT systems. Their strategic role ensures that the data environment is scalable, secure, and organized in a way that aligns with goals and facilitates easy access and analysis.

  • Database administrators: tasked with the management, maintenance, and security of databases. They ensure that databases run efficiently and without interruption. They handle backup and recovery, tuning database performance, and managing data permissions. DBAs play a crucial role in ensuring that the storage and retrieval of data are handled seamlessly, supporting the broader data infrastructure that the R&D teams rely on.