Senior Business Intelligence Analyst
Role Overview
The Senior Business Intelligence Analyst defines, designs, and implements end-to-end use cases on a global reporting platform and cross-functional data repository.
The role uses analytics, visualization, and AI to turn platform data into business value and acts as a solution architect and technical authority.
Key Skills for This Role
Full Job Posting
Role overview
The Senior Business Intelligence Analyst defines, designs, and implements end-to-end use cases on a global reporting platform and cross-functional data repository.
The role uses analytics, visualization, and AI to turn platform data into business value and acts as a solution architect and technical authority.
Architecture and delivery
- Own reporting-platform solution architecture for ingestion, transformation, semantic models, analytics, and consumption layers.
- Design scalable, secure architecture patterns and translate business requirements into feasible, performant, maintainable technical designs.
- Lead architectural decisions for capabilities, enhancements, and integrations, evaluating cost, performance, and complexity trade-offs.
- Assess feasibility and lead proofs of concept for new requirements, technologies, and architecture patterns.
- Guide ETL implementation with the Data Foundation team and build semantic layers on database, data lake, and data warehouse layers.
- Maintain logical, physical, and data-flow documentation.
Governance and enablement
- Embed data governance, security, and access control in solution designs.
- Support technical onboarding and adoption, ensuring solutions are intuitive, performant, and fit for purpose.
- Oversee support, incidents, and enhancements, ensuring root causes are addressed structurally.
Knowledge and attributes
- Requires advanced analytical ability and the ability to turn ambiguous business problems and complex data into clear, decision-ready insights.
- Requires strong knowledge of business intelligence, data architecture, semantic modeling, visualization, and enterprise analytics delivery.
- Requires knowledge of data governance, data quality, data protection, privacy, security, and access control.
- Requires proficiency in Excel, Power BI, SQL-based analysis, semantic models, and DAX; knowledge of modern cloud data platforms is also sought.
- Requires communication, presentation, collaboration, stakeholder influence, attention to detail, ownership, organization, and independent coordination across teams.
Academic qualifications
- A bachelor’s degree in a relevant discipline, including computer science, information systems, data analytics, business intelligence, engineering, mathematics, statistics, finance, business administration, or a related field, is specified.
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