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DATA ANALYST
3. KEY RESPONSIBILITY
- Engage stakeholders to translate business questions into measurable KPIs, metrics, and user stories; document acceptance criteria and define standard aggregations per the KPI master standard.
- Design intuitive, role-based report experiences aligned to DP World visualization standards and accessibility best practices.
- Build clean, performant star-schema models and semantic layers; develop measures with DAX and transformations with Power Query (M) or dataflows; apply data types, formats, and hierarchies consistently
- Implement incremental refresh, composite models, and DirectQuery/Import strategies; optimize with aggregations where needed.
- Develop interactive reports and dashboards in Power BI Desktop following storytelling and visual design best practices; use field parameters, bookmarks, and tooltips for guided analysis.
- Standardize KPI cards, visuals, themes, and nomenclature for cross-report consistency.
- Implement Row-Level Security (RLS) and Object-Level Security (OLS); manage workspaces, datasets, and lineage in Power BI Service.
- Adhere to naming conventions, documentation standards, and data governance policies; validate logic against golden sources.
- Establish data validation checks and reconcile to source-of-truth; remediate data quality issues with source teams.
- Use Power BI Deployment Pipelines (Dev/Test/Prod) and ALM Toolkit for schema diff/merges; integrate with version control (e.g., Git) where applicable.
- Monitor refresh reliability, model size, and performance (DAX Studio/Performance Analyzer); maintain SLAs and optimize load times.
- Create release notes, data dictionaries, and how-to guides; conduct enablement sessions for business users and WeOne reporting champions.
- Track usage metrics, drive adoption, and iterate based on feedback and telemetry.
- Work with Transformation, Finance, Operations, Commercial, and IT Data Platform to prioritize backlog and deliver value in sprints.
4. TECHNICAL COMPETENCIES
Reporting & Modeling (Power Platform – Reporting)
- Power BI Desktop & Service: datasets, dataflows, semantic models, RLS/OLS, deployment pipelines, workspace mgmt.
- DAX / Power Query (M): advanced measures, calculation logic, query folding, transformations.
- Data Modeling: star schema, slowly changing dimensions, hierarchies, aggregations, incremental refresh, composite models.
- Performance Tuning: DAX optimization, model size reduction, summarization tables, Performance Analyzer, DAX Studio. Visualization Standards: storytelling, accessibility, design patterns, corporate themes.
Data & Platform
- SQL (Azure SQL/Synapse), files in Data Lake Gen2, optional: Fabric/OneLake if in scope. Tools: Tabular Editor, ALM Toolkit, DAX Studio; optional: Power BI REST API; basic Python/Excel for ad hoc.
Delivery & Governance
- Agile delivery: backlog, sprint planning, user stories, acceptance criteria. Documentation & Data Governance: lineage, glossary, data dictionary, usage metrics.
IT Project Management
IT Innovation
5. FUNCTIONAL RELATIONSHIPS
Transformation Office (WeOne), Finance, Operations, Commercial, HSE, HR Analytics, Corporate Strategy/PMO, IT Data Platform/Security, Internal Audit (as needed), and external partners/vendors.
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