Fabric Data Engineer

Build the modern data backbone a global travel-rewards business runs on, work hands-on with the newest Microsoft Fabric and AI tooling, and coach the engineers coming up behind you.

About the Rolearrivia is looking for an experienced Fabric Data Engineer to take ownership of complex data pipeline architectures inside the Microsoft Fabric ecosystem. You will design and optimize enterprise-scale data solutions, set the technical standards the team works to, and mentor junior engineers along the way.

This work matters right now. You will help migrate an existing on-premise relational database into our modern cloud environment and play an instrumental role in decommissioning legacy data-warehouse systems. The pace is accelerating, and your pipelines are what let the business rely on accurate, up-to-date reports and dashboards.

Your impact reaches across the company. You will partner with analysts, data scientists, and business stakeholders to turn complex requirements into reliable, performant, well-governed data platforms, and the standards you set will shape how the whole team builds.

It is also a genuinely modern role. At arrivia, we are committed to AI-driven innovation, and you will work alongside the latest AI technologies, using LLMs, Model Context Protocol servers, and AI-assisted tools to accelerate delivery and raise engineering quality. You will also get flexible and hybrid work, certification support, and a clear path to grow into Senior, Lead, and Principal roles.

What You'll Own

• Pipeline architecture: Architect and optimize end-to-end pipelines with Microsoft Fabric Data Factory, Dataflows Gen2, and PySpark and Spark SQL notebooks, built for scale and performance.

• Lakehouse and warehouse design: Lead Lakehouse and Warehouse design on the medallion (Bronze, Silver, Gold) pattern, and set the best practices the team follows.

• Cloud modernization: Help move on-premise relational data into OneLake and retire legacy data-warehouse systems, accelerating the shift to a modern cloud platform.

• Real-time ingestion: Build low-latency streaming pipelines with Fabric Eventstream from sources such as Azure Event Hubs, IoT Hub, and custom applications.

• Performance and reliability: Write highly optimized T-SQL, Spark SQL, and PySpark, and own incremental loads, refresh scheduling, and SLA monitoring so pipelines stay dependable.

• AI-augmented engineering: Design pipelines that support Retrieval-Augmented Generation, including chunking, embeddings, and vector search, and use LLMs and MCP servers to speed up and improve how the team works.