This role involves architecting and leading enterprise analytics solutions leveraging Microsoft Fabric. You will be instrumental in building scalable Lakehouse architectures, driving Data Engineering workloads, and developing advanced Real-Time Intelligence and Power BI solutions. A key aspect will be ensuring robust governance and optimal performance, alongside guiding and mentoring junior team members.

As a Senior Microsoft Fabric Engineer or Fabric Technical Lead, you will be the driving force behind innovative data solutions. Your expertise will shape the future of our analytics capabilities.

- Design and implement enterprise-scale Microsoft Fabric solutions. - Architect scalable Lakehouse, Warehouse, and One Lake environments using Medallion Architecture. - Develop and optimize Fabric Notebooks with Python, PySpark, and Spark SQL. - Lead reusable Python framework development and notebook-based ETL/ELT. - Optimize Spark job performance and distributed data processing. - Build and maintain Data Factory Pipelines, Dataflows Gen2, and orchestration. - Develop enterprise semantic models and Power BI reporting. - Integrate data from diverse sources including SQL Server, Oracle, SAP, Azure Data Lake, and REST APIs. - Implement CI/CD, Git integration, and deployment pipelines. - Troubleshoot complex production issues across various Fabric components. - Mentor junior engineers on Fabric development and best practices. - Collaborate with stakeholders to deliver analytics solutions. - Prepare technical documentation and operational runbooks.

A minimum of 6 years of experience in data engineering and analytics is required for this Senior Microsoft Fabric Engineer / Fabric Technical Lead position. Proficiency in designing and implementing large-scale analytics solutions using Microsoft Fabric is essential. You must have strong skills in Python, PySpark, and Spark SQL for developing and optimizing data pipelines and notebooks.

Experience with architectural patterns like Medallion Architecture (Bronze, Silver, Gold) within Lakehouse or Warehouse environments is crucial. The role also demands expertise in building Data Factory Pipelines, Dataflows Gen2, and managing CI/CD processes with Git integration. A proven ability to integrate data from various enterprise platforms and troubleshoot complex production issues is necessary.

Candidates should also possess strong data modeling skills and the ability to develop enterprise semantic models for Power BI. Experience in mentoring junior engineers and collaborating effectively with cross-functional teams and business stakeholders is highly valued. Strong communication skills for preparing technical documentation are also expected.