Maintain up-to-date data models and logical and physical data structures, keeping them consistent with business rules.
Ensure metadata quality, considering its usefulness to the company's various business units.
Participate in the evaluation of automation solutions whenever they affect the production and use of information; monitor the implementation of models and verify the quality of database content to ensure alignment with business objectives.
Define conceptual, logical and physical modeling of the information required to meet business needs.
Develop, propose, maintain and update data models, ensuring data normalization, eliminating or minimizing redundant data, and promoting data consistency at the model level for implementation in the database.
Define data access security procedures.
Redefine data models based on particularities of the physical implementation to improve database performance.
Identify data distribution requirements and work with DBAs on physical implementation.
Work on architecture modeling and deployment of BI & Big Data systems and on indicators and dashboards to support executive decision-making.
Design and develop the architecture for data services across the technology and platform ecosystem (Relational, Analytical, NoSQL) to support data consumption by BI applications.
Promote and develop BI best practices, with a results- and delivery-oriented approach, providing consulting, support and mentoring to various business areas, offering recommendations and guidance for continuous improvement and sustaining the established organizational model.
Participate in the development and update of data management and governance methodology.
Support the specification of integration mechanisms such as services, ETL specifications, database links and other integration methods via DBMS.
Write SQL scripts for data validations, report specifications, etc.
Requirements
Bachelor's degree in Information Technology, or completion of any higher education degree accompanied by a postgraduate certificate (specialization, master's or doctorate) in Information Technology of at least 360 hours.
Experience in data modeling and integration of large volumes in analytical and transactional environments.