• Estruturar e documentar processos da área de Engenharia de Dados • Acompanhar demandas, entregas e rotinas operacionais • Definir, consolidar e monitorar indicadores e KPIs • Realizar consultas e análises em SQL para levantamento e validação de dados • Organizar informações e elaborar materiais executivos e apresentações para comunicação de indicadores, resultados e evolução das iniciativas • Conduzir ou apoiar reuniões de acompanhamento, ritos e status de indicadores • Apoiar a comunicação das entregas e resultados da Engenharia de Dados para liderança e áreas parceiras • Atuar em parceria com times técnicos e áreas interfaces para dar visibilidade às entregas e apoiar a evolução dos processos

Role Description The GRC Data & Risk Analytics Analyst supports the Assurance function by helping organize, document, and prepare data used in Governance, Risk, and Compliance (GRC) reporting. This role contributes to improving the quality, consistency, and usability of information used by Assurance, Cyber, and Enterprise Risk Management teams. This is a supporting analytical role. The student will assist with data organization, documentation, and reporting preparation. The role does not involve setting risk thresholds, defining performance targets, or making risk decisions. Key Responsibilities - Document relationships between GRC records such as risks, incidents, and third parties. - Assist with preparing draft dashboards and reports for review. - Support validation of data used in risk and compliance reporting. - Assist with organizing audit and compliance evidence. Example Outputs (Illustrative) - Document risk, incident, and third-party records relate within the GRC system. - Build dashboards or report views for review by Assurance leadership. - Structured datasets or tables used to support risk, compliance, or audit reporting. - Organized audit or compliance evidence with clear traceability to risks and controls. Qualifications - Strong analytical and quantitative mindset, with coursework or experience in statistics, data analysis, or related fields. - Basic understanding of relational data concepts (e.g., tables, relationships). - Comfortable working with structured datasets and documentation. - Programming experience (e.g., Python) is an asset but not required. - Interest in governance, risk management, cybersecurity, or compliance. Technical Exposure (Assets, Not Requirements) - Data analysis tools (e.g., Python, Excel, Power BI, Zoho Analytics). - Low-code / no-code platforms (e.g., Microsoft Power Platform, Zoho Creator). - Diagramming tools (e.g., Microsoft Visio). - AI-enabled productivity tools used for analysis and documentation. Tools & Environment - Corporate laptop. - Microsoft 365 (Excel, SharePoint, Power BI). - Access to the GRC system. - AI-enabled productivity tools. - Supervision by Assurance leadership. Benefits - 🌍 Flexible Ways of Working: Design your workday around what matters most. With flexible hours, you can balance work with all the other important things in life. And, with our Remote Work Arrangement, you can work from anywhere in the world for part of the year—whether that’s a beach in Bali or your cozy cabin in Muskoka. - 🚀 Career Development That Moves You Forward: Fuel your growth with funding for courses, certifications, and conferences. Explore new horizons through job rotations and secondments, and benefit from ongoing coaching and personalized development planning that keeps your career moving. At Embark, people stick around for the long-haul. - 🎉 Fun Is Part of the Job: We take fun seriously. From themed parties and surprise treat days to team socials that actually make you want to show up, we create moments that spark joy, build connection, and make work feel like more than just work.

• Build and maintain dbt models that transform raw source data into reliable, well-documented, tested analytical assets used across the business • Partner with stakeholders across Operations, Finance, Marketing, Sales, and Product to translate ambiguous business questions into precise analytical deliverables. You should be able to identify if the ask needs refinement before the work begins • Design and ship Tableau dashboards and data products that automate reporting that currently requires manual effort, permanently removing recurring analytical burden from the team • Identify gaps in our data coverage and work with engineering or independently to close them — whether that means writing a Python ingestion pipeline or modeling a new source • Maintain data quality standards across the warehouse: write dbt tests, monitor for anomalies, and ensure that the numbers stakeholders see are trustworthy • Contribute to the team's analytical infrastructure. This means shared macros, source definitions, documentation standards, and CI/CD practices. • Stretch into data engineering or data science as business needs demand and for your own personal development: pipeline development, ML feature preparation, or predictive modeling are all on the table for the right candidate

• Analyze complex revenue, margin, CTR, conversion rates and other financial metrics; • Interact (in a clear and effective way) with different business areas and teams; • Execute complex seasonal studies and help to create relevant client-oriented material; • Maintain complex reports in support of Account Management and Sales teams; • Help Account Management and Technical Support teams with campaign optimization and strategies, providing on-demand analysis.