Owns end-to-end Microsoft Fabric and Power BI architecture, from Oracle and JD Edwards ingestion through Lakehouse, Warehouse, semantic models, governance, and certified data products. Designs and builds Fabric pipelines, Spark notebooks, Delta optimizations, enterprise Power BI models, security, CI/CD, capacity management, and monitoring. Establishes architecture standards, reviews code, optimizes performance and costs, and mentors engineering, BI, and analytics teams.
Data & Analytics Architect — Microsoft
Fabric & Power BI
Experience: 10+ years (3+ in Fabric or
equivalent Azure data platform)
Role Summary
You are the end-to-end technical authority
for our analytics estate — from Oracle/JD Edwards source systems through
ingestion, Lakehouse and semantic layer, to certified Power BI data products.
The role spans the full Microsoft Fabric stack and enterprise Power BI
architecture, with a hands-on build component alongside the design work.
What You'll Do
- Own the target-state Fabric architecture: workspace/domain
topology, OneLake structure, medallion layering, and Lakehouse vs.
Warehouse vs. Eventhouse decisions.
- Design and build Fabric Data Factory pipelines and Spark
notebooks (PySpark/Spark SQL) metadata-driven ingestion, orchestration,
Delta table optimisation, error handling and monitoring.
- Architect ingestion from Oracle / JD Edwards: incremental and
CDC extraction, gateway connectivity, reconciliation back to ERP
source-of-truth.
- Architect enterprise semantic models — star schemas, Direct
Lake vs. Import vs. Direct Query, advanced DAX, performance tuning at
scale.
- Define Power BI governance: RLS/OLS, Entra ID group strategy,
certified datasets, workspace and tenant settings, gateways, licensing.
- Establish CI/CD via Fabric Git integration and deployment
pipelines, own Fabric capacity sizing, monitoring and cost optimization.
- Set standards, review code and architecture, and mentor
engineers, BI developers and analysts.
Must Have
- Microsoft Fabric, full stack, hands-on: One Lake,
Lakehouse/Delta, Warehouse, Data Factory pipelines, Dataflows Gen2,
Notebooks, semantic models, Direct Lake.
- Power BI at architect level (6+ yrs): dimensional modelling,
advanced DAX and optimization, RLS/OLS, enterprise governance and ALM.
- Oracle Database: strong SQL and PL/SQL, query tuning, and
proven extraction from large normalized ERP schemas.
- Advanced SQL, solid Python, Spark tuning, Git-based CI/CD.
- Azure fundamentals (Entra ID, ADLS Gen2, Key Vault) and Fabric
admin/security model.
- Clear communication with both engineering and business
stakeholders; strong documentation discipline.
Good to Have
- JD Edwards EnterpriseOne functional knowledge — Finance,
Distribution and/or Manufacturing; familiarity with F-tables (F0911,
F4211, F0411), UDCs, Julian dates and JDE data conventions.
- Microsoft certifications : DP-600 /
DP-700, PL-300.
- Experience migrating legacy data and analytics platforms to
Fabric
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