The Role
:
We are looking for a client-facing Data Consultant who can design, build, and optimise modern data platforms and analytics solutions using the Microsoft data stack, with a strong emphasis on Microsoft Fabric. You’ll work across data ingestion, transformation, modelling, governance, and visualisation—translating business needs into robust, secure, scalable solutions that deliver measurable outcomes. This person must be comfortable speaking to client and internal teams on technical matters.
The Data Consultant will be responsible for:
Delivery & Engineering
1. Design, build, and optimise data pipelines and architectures using Microsoft Fabric and adjacent Azure data services.
2. Implement ingestion and transformation patterns in Fabric using Lakehouse, Pipelines, and Notebooks, ensuring data is accessible, well-organised, and high-quality.
3. Build and maintain scalable data processing systems that transform complex datasets into trusted, analytics-ready assets.
4. Establish practices for data quality measurement, monitoring, and feedback loops across ingestion/migration activities.
Analytics & Semantic Modelling
5. Create and enhance Power BI semantic models (relationships, measures, security rules).
6. Implement data-access controls for analytical consumption (e.g., row-level/object-level security patterns in semantic models).
7. Develop insightful reporting and analytics experiences in Power BI to augment client decision-making and operational outcomes.
Architecture, Governance & Standards
8. Translate business requirements into end-to-end data architecture, balancing performance, cost, security, and maintainability.
9. Apply and advise on security patterns and contribute to governance-by-design.
10. Enforce technical documentation standards, architectural artefacts, and implementation patterns that improve repeatability and delivery quality.
Consulting, Stakeholders & Pre-sales
11. Engage stakeholders to shape problem statements, clarify requirements, and define pragmatic delivery approaches.
12. Support scoping, estimation, and delivery planning; produce high-quality client-facing documentation and presentations.
13. Collaborate with adjacent teams (e.g., Dynamics/Power Platform/AI) to integrate analytics and data capabilities into broader solutions.
14. Stay current with Fabric capabilities and the evolving Microsoft data ecosystem, bringing innovation into client solutions.
Required Skills & Experience
Microsoft Data Stack
15. Hands-on experience delivering data solutions with Microsoft Fabric, including Lakehouse, Pipelines, and Notebooks/Spark-based processing.
16. Strong capability in data pipeline and architecture design and optimisation across Microsoft tooling (Fabric and/or other Azure services).
17. Strong Power BI capability (reporting + modelling) and ability to connect engineering outputs to analytics consumption.
18. Understanding of Direct Lake semantic modelling design considerations (model creation, table choices, and enforcing access rules).
19. Proven experience with ingestion and transformation patterns (ETL/ELT concepts), data modelling, and delivering analytics-ready datasets.
20. Ability to implement approaches that improve delivery reliability: data quality checks, monitoring, and operational feedback mechanisms.
Consulting & Communication
21. Strong written and verbal communication, able to present technical concepts clearly to mixed audiences.
22. Strong relationship-building and stakeholder management in complex client environments.
Code Management
23. CI/CD for Fabric items.
24. Git-based workflow.
25. Testing frameworks.
26. Performance tuning patterns.
27. Cost/capacity optimisation.
Desirable Skills & Experience
28. Experience across adjacent Microsoft services often paired with Fabric (e.g., Azure Synapse Analytics, Azure Data Factory, Azure Databricks, Azure Data Lake).
29. Familiarity with Microsoft Purview and broader governance practices.
30. Dynamics 365 CE and FO integration and analytics.
31. Exposure to AI/ML enablement in Microsoft ecosystem (e.g., Azure ML / AI Foundry / Azure OpenAI), particularly where analytics feeds AI-powered apps.
32. Experience designing BI / data analytics solutions and enforcing architecture/documentation standards.
The Person:
33. Strong technical skills.
34. Experience of delivering client engagements.
35. Experience in a consultancy or customer facing role.
36. An intelligent, analytical and pragmatic approach to problem solving.
37. Excellent relationship building skills with clients and colleagues.
38. Excellent interpersonal skills and the ability to influence and manage a range of relationships in a complex environment.
39. Strong communication skills (verbal, written and listening): an ability to present information concisely, to communicate in a manner applicable to all levels.
40. Able to produce high quality and professional technical documentation.
41. Excellent attention to detail and ability to ensure documents are consistent in language, terminology and style.
42. Flexible approach to work with a focus on delivery to deadlines and high standards.
43. Ability to handle highly confidential information with tact and discretion.
44. Be able to achieve SC security clearance.