Senior Fabric Data Engineer designing and optimizing data solutions using Microsoft Fabric for diverse clients. Collaborating with teams and mentoring junior engineers in data platform initiatives.
Responsibilities
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).
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.
Senior Data Engineer at Keyrus leading the design, development, and delivery of scalable data platforms. Collaborating with teams to translate requirements into production - grade solutions and mentoring engineers.
Senior Data Engineer for global payments platform designing ETL pipelines and data models. Collaborating across teams to tackle complex data challenges in an innovative fintech environment.
Data Warehouse Modelling Engineer designing and maintaining data models using Data Vault 2.0 for iGaming industry. Collaborating with stakeholders and optimizing data models in a hybrid work environment.
Senior Data Engineer driving impactful data solutions for the climate logistics startup HIVED's core data platform. Collaborating with cross - functional squads to enhance analytics and delivery.
Data Engineer developing and maintaining CRE forecasting infrastructure for Cushman & Wakefield. Collaborates with senior economists and technical teams to ensure high - quality data solutions.
Data Engineer at PwC, engaging with Azure cloud services to enhance data handling and integrity. Responsibilities include pipeline optimizations, documentation, and collaboration with stakeholders.
Data Engineer Manager at PwC focusing on building data infrastructure and solutions. Leading data engineering projects to transform raw data into actionable insights and drive business growth.