Microsoft Fabric Data Engineer #3621727

Join a technology-driven financial services environment supporting enterprise data transformation, governance, analytics, and reporting initiatives. This team is focused on modernizing how data is ingested, transformed, governed, and delivered through scalable Microsoft Fabric and lakehouse-based solutions. The environment is collaborative, technical, and delivery-focused, with an emphasis on building reliable data platforms that support business intelligence, operational reporting, and downstream analytics.

This is a hybrid opportunity based in Charlotte, NC, supporting a modern Microsoft Fabric data platform. The role offers the opportunity to work hands-on with lakehouse architecture, OneLake, Spark, PySpark, SQL, Delta Tables, data pipelines, and analytics-ready data delivery for Power BI and enterprise reporting users.

• Design, build, and maintain scalable lakehouse architecture using Microsoft Fabric and OneLake.
• Develop data ingestion, transformation, and delivery processes that support analytics, reporting, and downstream business consumption.
• Build and maintain end-to-end ETL/ELT pipelines across batch and real-time data sources.
• Integrate data from APIs, databases, enterprise systems, flat files, Jira, ERP, CRM, and streaming sources.
• Develop large-scale Spark jobs using PySpark and Spark SQL for batch and streaming workloads.
• Create and maintain notebooks for data transformation, analysis, cleansing, enrichment, and validation.
• Implement data quality controls to ensure datasets are accurate, reliable, and ready for Power BI and business intelligence use cases.
• Support structured, semi-structured, and unstructured data ingestion within a modern cloud-based data platform.

• 5–7 years of relevant data engineering, data development, or analytics engineering experience.
• Hands-on experience with Microsoft Fabric, including Lakehouse, OneLake, Pipelines, and Notebooks.
• Strong experience with Apache Spark, PySpark, and Spark SQL.
• Strong SQL and Python development skills.
• Experience building ETL/ELT pipelines for ingestion, transformation, and data serving.
• Experience with Delta Lake, Delta Tables, lakehouse architecture, and modern data platform design.
• Ability to integrate data from APIs, databases, streaming sources, enterprise systems, and flat files.
• Experience building data validation, cleansing, enrichment, and quality-control logic.
• Exposure to Power BI enablement and delivering analytics-ready datasets.
• Strong communication, problem-solving, and cross-functional collaboration skills.

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