Fabric Expert

Role: Fabric Expert

Position overview:
We are looking for a skilled Fabric Expert to design and deliver enterprise scale data and analytics solutions using Microsoft Fabric. This is a deeply hands-on role combining data engineering with architecture ownership. The successful candidate will personally build, optimize, and troubleshoot solutions across OneLake, Lakehouse/Warehouse, Fabric Data Factory, notebooks, SQL/PySpark, and Power BI semantic models, while also defining architectural patterns and engineering standards for the broader team.

The role requires someone who can move comfortably between architecture and implementation: making technology and design decisions, validating them through working solutions, resolving production issues, and establishing reusable patterns that other engineers can follow.

A key focus is the evolution of an existing enterprise BI and data landscape toward Microsoft Fabric while maintaining and improving the performance, reliability, and scalability of current Power BI and analytical workloads.

Roles and Responsibilities :

• Design and implement end-to-end Microsoft Fabric solutions across OneLake, Lakehouse, Warehouse, Data Factory, notebooks, SQL/PySpark, and Power BI.
• Build and evolve scalable medallion architectures, defining practical patterns for ingestion, transformation, storage, modeling, and consumption.
• Design and implement batch and incremental data pipelines across relational databases, files, APIs, cloud services, and other enterprise data sources.
• Build and optimize enterprise Power BI semantic models, including dimensional models, DAX, aggregations, incremental refresh, and appropriate use of Import, DirectQuery, Direct Lake, and composite models.
• Diagnose and resolve performance issues across data pipelines, Delta tables, SQL workloads, semantic models, reports, and Fabric capacity.
• Define and implement Fabric platform patterns covering workspaces, domains, environments, OneLake data sharing, security, governance, and deployment.
• Apply appropriate architectural and engineering patterns for structured, semi-structured, and large-scale analytical data workloads.
• Implement data quality, reconciliation, lineage, metadata, monitoring, and operational controls.
• Establish and maintain Git-based development, CI/CD, automated testing, deployment, and environment-management practices for Fabric workloads.
• Develop reusable engineering patterns, accelerators, and reference implementations that can be adopted by other teams.
• Support and optimize existing enterprise data and BI solutions while identifying appropriate opportunities for incremental modernization and migration to Fabric.
• Lead technical assessments and proofs of concept through working implementations and measurable outcomes.
• Provide technical leadership across data engineering, BI, architecture, infrastructure, security, governance, and business teams while remaining a direct contributor to implementation and production support.
• Maintain architecture documentation, data flows, technical standards, and implementation guidance based on the solutions and patterns delivered.