• Relevar y analizar requerimientos funcionales y de negocio. • Documentar procesos, historias de usuario y especificaciones funcionales. • Coordinar reuniones con stakeholders y equipos técnicos. • Identificar oportunidades de mejora y optimización de procesos. • Participar en el seguimiento y validación de desarrollos e implementaciones. • Colaborar en la definición de soluciones funcionales alineadas a los objetivos del negocio. • Acompañar pruebas funcionales y validación de entregables.

• The Data Management Analyst supports the Data Management team across database administration, reporting, automation, and enterprise data operations. • This role assists with the creation, maintenance, monitoring, and basic troubleshooting of databases and data platforms that securely store and manage large volumes of enterprise data. • The analyst supports data workflow automation, job scheduling, and report distribution processes to improve efficiency and reduce manual effort. • Working closely with senior data management, reporting, and analytics staff, the role contributes to system enhancements, process documentation, and responses to data-related requests. • Key responsibilities include assisting with data collection and analysis, documenting process flows, and implementing simple logic or code changes under guidance. • The role also supports database performance and data accuracy testing to ensure systems operate as intended. • Additionally, the Data Management Analyst helps maintain system documentation, operational procedures, and data standards, ensuring updates and improvements are clearly documented and aligned with organizational governance and business needs.

• Participate in a 10-week ServiceNow Business Process Consultant Training Program • Engage in hands-on exercises focused on business process analysis and ServiceNow • Collaborate with stakeholders to gather requirements and design processes • Support internal ServiceNow applications by documenting processes and identifying improvements • Prepare for ServiceNow certification exams and complete study programs

• Engaging with stakeholders to gather, define, and manage functional and non-functional requirements, supporting delivery through development, testing, and UAT activities. • Conducting data profiling and analysis to support data validation, quality, and understanding for Data Engineering and Data Modelling activities. • Supporting ETL processes by promoting best practices and validating data against Entity Relationship (ER) diagrams and data models. • Creating and maintaining clear, concise documentation and artefacts to support data knowledge and solution understanding. • Supporting Product Owners with stakeholder engagement, User Story and Task creation, data analysis, and solution delivery activities. • Working closely with Data Modelling and Data Engineering teams to support the design and implementation of data solutions, including dimensionally modelled Data Warehouses and Data Lakes using the Microsoft Azure technology stack, including Azure Databricks and Azure Data Factory. • Supporting testing activities through the creation of comprehensive test scenarios and test cases aligned to business requirements and user stories. • Supporting Power BI Development and Support activities by: • Gathering and documenting reporting requirements, including KPIs, metrics, filters, and business rules. • Translating business requirements into clear reporting specifications. • Validating report accuracy and consistency against underlying data sources. • Performing functional testing of reports and dashboards, including filters, slicers, drill-down and drill-through functionality. • Ensuring reporting outputs align with business requirements and agreed data models. • Acting as a liaison between business stakeholders and Power BI developers to support successful delivery. • Collaborating effectively with onshore teams, offshore teams, and external partners to deliver high-quality outcomes. • Supporting wider team delivery activities, including: • Providing effort estimates, tracking progress, and communicating status updates. • Logging and managing defects with clear descriptions, priorities, and severity levels. • Tracking defects through to resolution, validating fixes, and formally closing issues. • Escalating critical risks, issues, or data integrity concerns in a proactive and timely manner.