Senior Azure Data Engineer (SQL Server)
Summary
Senior Azure Data Engineer designs medallion lakehouse architecture for a multitenant SaaS platform, integrating LLMs for AI-driven reporting and tuning SQL Server performance.
We are looking for an experienced Azure Data Engineer with strong SQL Server expertise to design and implement a medallion lakehouse architecture for a multitenant SaaS platform. This is a 3 month engagement with the possibility of extension. This role is suited for a senior engineer who can operate as an architect and technical advisor, guiding stack decisions and supporting the wider engineering team, rather than a primarily hands-on coding role.
About the Project:
Our client operates a multitenant SaaS platform and is building out a medallion lakehouse architecture on Azure, most likely on Microsoft Fabric and OneLake, though the final stack is still open. The team is also integrating LLMs with existing data schemas to power AI driven reporting, and is looking for someone with genuine, current experience applying AI within engineering work rather than passive exposure to it.
Responsibilities:
- Designing and implementing bronze, silver, and gold data layers using medallion architecture on Azure;
- Designing and implementing data transformation pipelines for a multitenant SaaS platform;
- Tuning SQL Server performance and providing architectural guidance and support to engineering teams;
- Formulating structured requests to LLMs to integrate schemas for AI driven reporting, and assessing whether responses are accurate or hallucinated;
- Applying current, practical experience and a clear point of view on using AI within data engineering workflows.
Qualifications:
- Senior level experience designing and implementing medallion lakehouse architectures on Azure;
- Broad exposure across Azure data platforms (Fabric, Synapse, Databricks, or similar), with confidence to advise on stack choices;
- Strong SQL Server tuning and architecture experience;
- Demonstrated experience integrating LLMs with structured data schemas for reporting or analytics;
- Active, current use of AI tools in engineering work, with sound judgment on evaluating AI output quality;
- Excellent communication skills in English.
Recruitment Process:
- Initial interview with our recruitment team;
- Technical interview with the client;
- Final decision and offer.