Analytics Engineer

The Analytics Engineer plays a key role in bridging Data Engineering and Analytics functions, transforming raw data into trusted, business-ready datasets and insights. This role is responsible for designing and maintaining data models, semantic models, reporting solutions, and analytics assets that support business decision-making., Working closely with both technical and business stakeholders, the Analytics Engineer will help drive data quality, reporting standards and governance whilst supporting the organisation’s data platform strategy and migration to Microsoft Fabric., Data Engineering & Integration

• Develop, maintain, and optimise data pipelines using Azure Data Factory and Microsoft Fabric.
• Design and implement ETL/ELT processes to ingest, transform, and prepare data for reporting and analytics.
• Collaborate with Data Engineers to ensure data solutions are scalable, reliable, and aligned with best practices.
• Support data quality initiatives and implement validation and monitoring processes.
• Troubleshoot and resolve data integration and performance issues.

Data Modelling & Analytics

• Design, develop, and maintain dimensional data models and semantic models.
• Optimise semantic models for performance, usability, and scalability.
• Create trusted datasets that support consistent KPI reporting
• Apply industry best practices for data modelling, governance, and reporting standards.
• Support analytics and data science initiatives through data preparation and modelling activities.

Reporting & Visualisation

• Develop and enhance Power BI reporting solutions.
• Facilitate requirements gathering and wireframing sessions with business stakeholders.
• Translate business requirements into effective reporting and analytical solutions.
• Ensure reporting solutions are user-friendly, performant, and aligned with business objectives.
• Drive adoption of reporting standards and best practices.

Stakeholder Engagement

• Work directly with business users and senior stakeholders to understand reporting and analytical requirements.
• Present findings, recommendations, and solution designs to both technical and non-technical audiences.
• Support strategic initiatives through data-driven insights and recommendations.
• Build strong relationships across departments to promote data-driven decision making.

Mentoring & Knowledge Sharing

• Share knowledge and promote best practices across the wider data community.
• Contribute to documentation, standards, and governance processes.
• Participate in peer reviews and provide constructive feedback.

Technical Experience

• Strong experience with SQL, including complex query development, optimisation, and troubleshooting.
• Experience developing and maintaining solutions using Azure Data Factory.
• Strong experience with Power BI, including:
• Semantic model design
• DAX development
• Performance optimisation
• Data modelling
• Report development
• Workspace governance
• Experience conducting requirements gathering and wireframe development.
• Strong understanding of dimensional modelling techniques and analytics best practices.
• Experience working with Azure-based data solutions and cloud technologies including Azure Synapse Analytics.
• Experience supporting data governance, KPI standardisation, and data quality initiatives.

Communication & Collaboration

• Excellent communication and presentation skills.
• Experience engaging with senior leadership and business stakeholders.
• Ability to translate technical concepts into business-friendly language.
• Strong stakeholder management and relationship-building skills.
• Experience facilitating workshops and requirements-gathering sessions.
• Strong analytical and problem-solving skills.
• Proactive and self-motivated.
• Curious and eager to learn new technologies.
• Strong attention to detail.
• Collaborative and team-oriented.
• Able to balance technical excellence with business value.
• Comfortable working in a fast-paced environment with multiple priorities.

Leadership & Development

• Experience mentoring, coaching, or sharing knowledge with colleagues.
• Ability to support and guide less experienced team members.
• Commitment to continuous improvement and adoption of best practices.

Desirable Skills & Experience

• Experience with Microsoft Fabric (Lakehouse, Warehouse, Dataflows Gen2, Pipelines, Semantic Models).
• Experience with Python for analytics, automation, or data preparation.
• Experience implementing CI/CD and source control practices.
• Experience with data governance frameworks and metadata management.
• Experience working within agile delivery environments.
• Experience with MuleSoft integrations.
• Experience with Google BigQuery.
• Exposure to Data Science and Machine Learning models.
• Experience with Microsoft Purview.
• Understanding of AI and Generative AI technologies within the Microsoft ecosystem.