Reporting to the Manager, Business Intelligence, this role serves as a data enabler within the Data Culture Office (DCO-BI), supporting decision‑making across Forecasting, Strategy, Marketing, and Sales.
The Data Analyst translates business questions into well‑defined, reusable datasets that support self‑service analytics and reliable decision‑making. Working at the intersection of business and data engineering, the role focuses on data modelling, definition, and cataloguing, while partnering with Data Engineers to ensure data is properly structured, validated, and aligned to business needs.
Acting as a key point of contact for data‑related inquiries, the role helps clarify requirements, identify appropriate data sources, and guides how data should be interpreted. Ad‑hoc analysis is performed as needed, primarily to inform scalable data design rather than one‑off outputs.
Success is measured by the quality, consistency, and adoption of data assets that enable faster, more confident decision‑making. These datasets may also support downstream systems such as eCommerce, CRM, and AI platforms, requiring strong standards for accuracy and reliability.
Roles, Responsibilities, and KPIs
- Design and deliver structured, reusable datasets to support business decision‑making.
- Define metrics, data structures, and analytical perspectives across domains and platforms.
- Build and maintain dashboards and reports for self‑service analytics.
- Conduct targeted ad‑hoc analysis to validate assumptions and inform scalable solutions.
- Collaborate with Data Engineers to ensure data quality and validation.
- Maintain clear documentation, definitions, and data catalogues.
- Translate business needs into data requirements and analytical approaches.
- Support data literacy and proper use of datasets across stakeholders.
- Promote reuse, consistency, and long‑term sustainability of data assets.
- Support identification of key business decisions tied to datasets and KPIs.
- Ensure analytics outputs connect to business actions and measurable outcomes.
- Contribute to scenario analysis and decision‑support use cases.
- Design data assets to support evolving consumption patterns, including AI‑assisted analytics and downstream decision systems.
Qualifications
- Experience working with complex datasets and preparing data for business use.
- Proficiency in SQL for data exploration and validation.
- Understanding of data modelling, metrics, and reusable data design.
- Experience with dashboard/reporting tools (e.g., Power BI, Tableau, Looker).
- Ability to translate business questions into data requirements.
- Strong communication skills for both technical and non‑technical audiences.
- Attention to data quality and consistency.
- Organized, adaptable, and able to balance short‑and‑long‑term priorities.
- Understanding of how data and analytics support business decision‑making.
- Familiarity with scenario analysis, forecasting, or decision‑support use cases.
- Exposure or interest in AI/ML or data‑driven automation.
Desirable
- BI/analytics experience in cross‑functional environments.
- Familiarity with data pipelines or analytics engineering concepts.
- Interest in automation or AI‑driven analytics.
- Experience using Python for data manipulation, automation, or analytical use cases.
- Exposure to developing VBA solutions to optimize and automate reporting workflows.
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