Fabric Data Engineer

Role Overview

• Design, build, and optimize enterprise-grade data solutions using Microsoft Fabric.
• Collaborate with cross-functional teams to deliver high-quality data solutions.
• Mentor junior engineers and share best practices in Data Engineering.
• Develop Lakehouse architectures and implement data pipelines for various workloads.
• Integrate and utilize Power BI for enterprise analytics solutions.

Requirements

• 7–10+ years of experience in Data Engineering.
• Strong hands-on experience with Microsoft Fabric, including at least one production implementation.
• Design and development of Lakehouse architectures using Microsoft Fabric, including OneLake, Delta tables, and Medallion architecture.
• Development of Dataflows Gen2, Notebooks (PySpark / SQL), and Pipelines for data ingestion, transformation, and orchestration.
• Implementation of end-to-end data pipelines using Data Factory (Fabric), Spark notebooks, and streaming workloads.
• SQL (Advanced/Expert) and PySpark / Spark SQL.
• Design of high-performance data pipelines for batch and real-time workloads.
• Development of semantic models and governed datasets to support enterprise analytics.
• Collaboration with Power BI developers to design DAX measures, relationships, and optimized data models.
• Implementation of Git integration and deployment pipelines for Fabric workloads.
• Experience with Eventstream, Real-Time Hub, or KQL (Nice to have).
• Experience implementing data governance frameworks, lineage, cataloging, and metadata management using tools such as Purview (Nice to have).
• Strong collaboration experience working with cross-functional teams, including Data Scientists, BI Engineers, Domain Owners, and Business Stakeholders.
• Ability to mentor junior engineers and contribute to engineering best practices.
• Experience supporting modern data platform initiatives and contributing to Centers of Excellence, reusable frameworks, and architectural standards.
• Experience with the Azure Data Platform ecosystem (ADLS, Azure Data Factory, Synapse, Databricks) (Nice to have).

Tech Stack

• Azure
• PySpark
• Spark
• SQL

Benefits

• WELLNESS: We promote personal, professional, and financial well-being.
• LET’S RELEASE YOUR POWER: Opportunities to specialize and grow across different technologies and domains.
• WE CREATE NEW THINGS: Freedom and support to design innovative data solutions.
• WE GROW TOGETHER: Participation in cutting-edge, multinational technology projects with diverse teams.