We are seeking a proactive and skilled Microsoft Fabric Data Engineer to join our growing team. In this role, you will be instrumental in designing, developing, and maintaining robust data solutions within the Microsoft Fabric ecosystem and delivering compelling solutions. If you are passionate about transforming data into actionable insights, building scalable data pipelines, and leveraging cutting-edge cloud technologies to solve complex business challenges, we encourage you to apply.
Key Responsibilities
- Design and implement scalable data pipelines using Microsoft Fabric components (Lakehouse, Data Factory, Notebooks, Dataflow Gen2, OneLake), Pyspark, Spark SQL, and Python for data ingestion, transformation, and loading.
- Design and maintain ETL processes to extract, transform, and load data into the Fabric Lakehouse, ensuring data is structured in a dimensional model for easy access and reporting.
- Develop optimized Power BI reports and dashboards, with proficiency in DAX formulas and Power Query, to deliver actionable insights to stakeholders.
- Monitor, troubleshoot, and optimize data pipelines, ensuring high performance and scalability with large datasets.
- Implement best practices for data security and compliance with privacy regulations throughout the data engineering lifecycle.
- Collaborate with stakeholders to define data needs and deliver tailored, self-service solutions.
The ideal candidate will possess
- Minimum 4 -5 years of experience in designing, implementing, and supporting Data and Business Intelligence solutions on Microsoft Fabric.
- Hands-on experience in design, development, and implementation of Microsoft Fabric, Azure Data Analytics Service (Azure Data Factory – ADF, Data Lake, Azure Synapse, Azure SQL, or Databricks)
- Hands-on experience in dimensional modeling, ETL, reporting tools, data governance, data warehousing, and structured and unstructured data.
- Experience in writing optimized SQL queries on MS Fabric or MS Azure Synapse Analytics (dedicated, serverless resources in queries, etc.)
- Experience with hybrid cloud deployments and integration between on-premises and cloud environments.