Senior Data Analytics Consultant
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Job Description
Senior Data Analytics Consultant shaping data solutions and analytics strategy for clients. Specializing in Azure data pipelines, semantic modelling, and reporting metrics.
Responsibilities:
- Shape end-to-end analytics architectures spanning ingestion, transformation, semantic modelling, and reporting.
- Design and build high-performance Fabric data pipelines, lake houses/warehouses, and Power BI datasets, reports, and dashboards following best practice standards.
- Apply data governance, security, lineage, and quality practices across Azure/Fabric and Power BI ecosystems, including workspace administration and controls within Power BI.
- Partner with customers to understand requirements and translate them into clear technical designs.
- Support testing, validation, and deployment of data and analytics solutions.
- Contribute to internal frameworks, accelerators, and delivery standards as part of a growing practice.
- Collaborate closely with peers, share knowledge, and continuously evolve your technical capability.
- Contribute to DevOps practices such as CI/CD for Fabric pipelines, semantic models, and Power BI assets.
Requirements:
- Strong hands-on experience with Azure data engineering tools such as Data Factory, Synapse, Data Lake, or Fabric.
- Strong Power BI capability including DAX, Power Query, data modelling, and design principles.
- Confidence working with SQL and modern data platform concepts.
- Experience translating business requirements into effective data and reporting solutions.
- Strong understanding of how data engineering, semantic modelling, and BI/reporting fit together in modern analytics architectures.
- Experience designing solutions that balance performance, governance, usability, and maintainability.
- Familiarity with data governance concepts such as workspace design, security models, access patterns, and content certification.
- Ability to advise customers on best practices across modelling, data architecture, and visualisation.
- A balanced skillset across data engineering, semantic modelling, and business intelligence, with the ability to work confidently across the full data and analytics lifecycle.
- Clear communication skills and the ability to engage with technical and non-technical stakeholders.
- A focus on quality, consistency, and continuous improvement.
- An interest in Microsoft Fabric and modern analytics approaches.
- Experience with Python or Power Platform is beneficial but not essential.
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