Data Warehouse
Plan, establish and govern central and structured repository that collects and integrates data from multiple systems (e.g., ERP, CRM, HR, finance, apps) and stores it in a consistent format so it can be queried efficiently for reporting, dashboards, and analytics.
Proficiency Level
Level 1 (Follow)
- Understand what a data warehouse is and basic concepts (tables, schemas, ETL or ELT, reporting).
- Run predefined queries/reports and follows SOP for accessing and extracting data.
- Handle data responsibly (uses correct datasets, avoids sharing restricted data).
Level 2 (Assist)
- Build and maintains standard tables/views; writes reliable SQL for routine analytics needs.
- Support scheduled data loads and basic data quality checks (nulls, duplicates, row counts).
- Document datasets and resolves common issues (failed jobs, missing fields) with guidance.
Level 3 (Apply)
- Design dimensional models (facts/dimensions) and implements ETL/ELT pipelines end-to-end.
- Implement data quality rules, lineage documentation, and performance optimisation (partitioning, indexing, clustering).
- Support stakeholders with curated datasets, semantic layers, and consistent KPI definitions.
Level 4 (Ensure)
- Architect scalable warehouse solutions (ingestion patterns, modelling standards, orchestration, security).
- Establish governance: data catalogue, access controls, naming conventions, SLA/monitoring, cost management.
- Lead complex initiatives (migration, consolidation, real-time/near-real-time pipelines) and mentors team.