Position Overview
Industry Platforms & Systems Integration (IP&SI) is trusted delivery practise - bringing together platform expertise, systems integration, modern data foundations, and security-by-design to help clients deliver change faster, with confidence. We connect trusted data, modernise core platforms, and uplift capability to reduce cost and risk while enabling resilient, artificial intelligence (AI)-ready operations.
The MDP Fabric Architect / Consultant / Developer designs, builds and operates modern analytics and data platforms using Microsoft Fabric, enabling scalable, governed, insight-driven data solutions across business intelligence (BI), analytics, data engineering and (where applicable) artificial intelligence (AI) workloads.
Depending on experience and seniority, the role may be hands-on in solution delivery (Developer/Consultant) or may lead platform architecture, standards and data strategy (Architect). The role partners with business stakeholders, data teams, cloud architects and security teams to ensure the platform is secure, scalable, cost-effective and operationally sound.
Key Responsibilities
- Design and implement data solutions using Microsoft Fabric, including OneLake, Lakehouse / Warehouse, Data Engineering, Data Factory, Data Science, Real-Time Analytics, and Power BI semantic models and reports.
- Build ingestion, transformation, and analytics pipelines using Fabric capabilities, supporting batch, streaming, and near real-time processing patterns.
- Develop and optimise data pipelines, lakehouse / warehouse models, and Power BI artefacts; apply strong Structured Query Language (SQL), data modelling, and analytical design practices.
- Implement data quality, lineage, and metadata practices; apply data governance using Microsoft Purview and Fabric capabilities.
- Support operations including monitoring, performance tuning, cost optimisation, environment management, deployment, and lifecycle management.
- Collaborate with business users, analysts, data teams, cloud architects, and security teams; advise on Fabric capabilities and design trade-offs, and contribute to documentation/runbooks and best practices.
Skills, Experience and Competencies
Technical Skills
- Strong expertise in Microsoft Fabric and modern lakehouse architecture (including OneLake, Lakehouse / Warehouse, and Fabric experiences such as Data Engineering and Data Factory).
- Experience with data ingestion, transformation, and analytics pipelines (batch, streaming, near real-time) using Fabric capabilities.
- Strong SQL, data modelling, and analytical design skills; ability to build and optimise lakehouse / warehouse models and semantic models.
- Experience with Power BI semantic models and reporting; ability to enable enterprise-grade analytics and reporting solutions.
- Understanding of data governance, security, monitoring, and cost optimisation in modern data platforms; ability to contribute to operational runbooks and best practices.
Experience (Role Level Determination)
MDP Fabric Architect
- 10–15+ years of data and analytics experience
- 7–10+ years designing enterprise data platforms
- Proven experience defining modern data strategies and platforms
MDP Fabric Consultant
- 6–9 years of data and analytics experience
- 4–6 years delivering modern data platforms (Fabric / Azure Synapse / Power BI)
- Strong delivery, design, and stakeholder engagement skills
MDP Fabric Developer
- 4–6 years of overall data / BI experience
- 2–4 years of hands-on experience with Microsoft Fabric, Power BI, or Azure data services
- Strong focus on implementation and development
Competencies
- Data product mindset, treating datasets, semantic models and reporting outputs as products with clear owners, consumers, quality measures and lifecycle management.
- Business-to-technical translation and collaboration, working with stakeholders and delivery teams to shape use cases and requirements, and translating them into practical Fabric design decisions and incremental delivery plans.
- Governance and security by design embedding access control, privacy, lineage and compliance requirements into the Fabric solution from the outset.
- Iterative, outcome-driven delivery executing value in increments (ingestion → lakehouse / warehouse → semantic model → reports), validates with users, and applies reusable patterns and automation to improve consistency.
- Quality, observability and operational readiness, applying testing, reconciliation and monitoring; produces clear documentation and runbooks to support sustainable operations.
