Senior Data Engineer - MS Fabric
RemoteUnited States
Job Summary
Design and implement modern Microsoft Fabric data platforms from architecture through production, building scalable ingestion, transformation, and orchestration pipelines that deliver trusted, high-quality data. Develop Lakehouse, warehouse, and semantic data models to support enterprise reporting, analytics, and decision-making while working directly with global customers to translate business challenges into practical technical solutions. Provide technical leadership across delivery teams through architecture guidance, mentoring, and the championing of modern engineering disciplines including source control, CI/CD, and automation. Collaborate with AI and software engineering teams to optimize data platforms for advanced analytics and future AI workloads, ensuring solutions are scalable, secure, and governed. This senior role blends hands-on engineering with consultative customer engagement to help organizations unlock the full value of their data and lay foundations for emerging AI capabilities.
Required Qualifications
- 4-6+ years' commercial experience delivering Data solutions
- Proven experience designing and implementing Microsoft Fabric solutions within enterprise environments
- Strong consulting skills, with experience working directly with customers to design and deliver technical solutions
- Strong SQL and Python development skills
- Experience designing modern cloud-based data platforms and enterprise data architectures
- Excellent communication skills and the ability to explain technical concepts to both technical and business stakeholders
- A collaborative mindset and a genuine passion for mentoring and sharing knowledge
- Modern Data Platforms - Designing and delivering Lakehouse, Warehouse and enterprise data solutions using Microsoft Fabric and the Azure data ecosystem, with a strong focus on scalability, governance and performance
- Data Engineering & Integration - Building robust ingestion, transformation and orchestration pipelines using technologies such as Data Factory, Spark, PySpark and SQL to deliver trusted, production-ready data
- Analytics & Modelling - Developing semantic models, dimensional models and curated data products that enable reporting, self-service analytics and business intelligence through Power BI and related technologies
- Engineering Practices - Applying modern software engineering principles including Git, CI/CD, testing, automation, Infrastructure as Code and operational monitoring to deliver reliable, maintainable data platforms
Desired Qualifications
- Supporting data platforms that underpin AI, machine learning or natural language processing workloads
- Exposure to Azure AI, Azure Machine Learning or Microsoft's AI ecosystem
- Experience working alongside AI or Data Science teams to prepare and optimise data for intelligent applications
- Databricks or other large-scale distributed data processing platforms
- Microsoft Data, Fabric or AI certifications
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