Data Platform & Analytics Lead - Microsoft Fabric in Manchester

The Data & Analytics Lead owns my clients' enterprise data platform and is responsible for ensuring it supports analytics, AI, and machine learning use cases in a structured, governed, and scalable way. This includes end-to-end accountability for data ingestion, transformation, lakehouse design, semantic modelling, and the development of reliable data products. The role ensures business data is accessible, consistent, and trusted, with clearly defined metrics that enable high-quality analysis, automation, and decision-making. It also establishes a strong platform foundation that accelerates the adoption of AI and advanced analytics, while maintaining appropriate governance, performance, and control.

Responsibilities:

• Data Platform & Lakehouse Architecture: Own the design and operation of the data platform within Microsoft Fabric. Define and implement lakehouse architecture patterns, including data layering, structure, storage and organisation. Manage ingestion, transformation and storage of data across the platform. Ensure the platform supports both analytical and AI/ML workloads.
• Data Modelling & Semantic Layer: Define and maintain core business metrics and calculations. Ensure consistent definitions across all datasets and outputs. Develop and manage semantic models used by the business. Ensure data structures are suitable for both analytics and machine learning use.
• Data Products & Analytics: Deliver structured datasets and analytical outputs aligned to business requirements. Maintain and enhance existing reporting and analytics solutions. Ensure outputs are aligned to operational processes and clearly understood. Reduce duplication and fragmentation of data across the organisation.
• AI & Machine Learning Enablement: Define how AI and machine learning will operate on the data platform. Ensure data is structured, accessible and governed to support AI/ML use cases. Identify and develop repeatable patterns for applying AI/ML to business data. Enable integration of AI outputs into existing data products and workflows. Ensure AI/ML outputs are traceable, controlled and aligned with defined metrics.
• Delivery Ownership & Roadmap: Take ownership of the current data platform implementation. Assess current architecture, datasets and capabilities. Maintain and prioritise the existing backlog, incorporating new requirements. Define and maintain a forward-looking roadmap for data platform and AI capability. Establish a structured delivery approach aligned to business priorities.
• Governance & Control: Implement data ownership, stewardship and access controls. Ensure documentation, version control and change management are maintained. Maintain auditability and traceability of data, calculations and AI outputs. Ensure appropriate control frameworks are applied to AI and machine learning usage.
• Stakeholder Engagement: Work with business stakeholders to define data and AI requirements. Translate requirements into structured data and platform capabilities. Ensure outputs are aligned to business processes and decision-making needs.

Person, Skills & Experience:

• Strong experience with Power BI, including data modelling, DAX and semantic model design.
• Hands-on experience with Microsoft Fabric, particularly lakehouse architecture, notebooks and data pipelines.
• Strong understanding of Apache Spark / PySpark and large-scale data processing.
• Experience designing and operating modern data platforms.
• Experience developing or enabling AI and machine learning capabilities using business data.
• Strong understanding of data preparation, feature engineering and model evaluation.
• Experience with Python-based data and ML tooling, e.g. Pandas, NumPy and scikit-learn.
• Experience with ML tooling within Microsoft Fabric or Azure, e.g. MLflow, notebooks, SynapseML or equivalent.
• Ability to structure data for AI/ML use and integrate outputs into business processes.
• Proven ability to assess, design and evolve data platforms in a structured manner.

Nice to haves:

• Experience with Azure OpenAI or adjacent AI services used within governed enterprise environments.
• Experience productionising ML solutions, including monitoring and lifecycle management.
• Experience working with unstructured or semi-structured data in a lakehouse context.
• Experience defining standards for reusable data products and AI-ready datasets.

What you get:

• Competitive salary with the ability to progress.
• 23-days holiday allowance, increasing with length of service, plus bank holidays, an extra day off on your birthday and the option to buy more!
• Company pension scheme.
• 2 paid leave days per year to volunteer and support your local community.
• Health cash plan with free access to a confidential Employee Assistance Programme (EAP).
• Life assurance.
• Cycle to work scheme, electric vehicle scheme, home and tech scheme, and retail discounts.
• Long service recognition to celebrate all the milestones.
• Beer (or soft drinks) and Pizza at the end of month, dress down every day, social events such as Summer BBQ, Christmas party and lots more!