Role & responsibilities

- Build and maintain data pipelines on Microsoft Fabric to ingest data from enterprise systems into OneLake, keeping it clean, structured and reliable.
- Design and manage Lakehouse structures, understanding what data exists, what it means, and how it should be organised for downstream systems.
- Work with the engineering team to ensure the right data reaches AI agents at the right time and in the right shape.
- Build Power BI dashboards and reports that give stakeholders clear operational visibility.
- Understand the business context behind the data and ask the questions that help the team build the right solution.
- Take ownership of pipeline health by monitoring, troubleshooting and resolving failures, and communicating root cause and resolution clearly.

Preferred candidate profile

Required Skills

- Hands-on experience with Microsoft Fabric on at least one real project (Pipelines,



Lakehouse or Power BI).
- Solid data literacy, with the ability to read a schema or dataset, understand the business behind it, and spot anomalies proactively.
- Strong SQL and working knowledge of Python/PySpark for debugging and transformations.
- Clear communication, including explaining data issues to non-technical stakeholders and writing concise incident summaries.
- Ownership mindset and the ability to learn new tools quickly (Azure AI Foundry, agent frameworks, RAG pipelines).

Good to Have

- Exposure to Azure Data Factory, Event Hub, Azure AI Search and Cosmos DB.
- Experience in client-facing or consulting environments.
- Exposure to AI/LLM projects and an understanding of what makes data AI-ready.”

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