Senior MS Fabric Data Engineer – Azure

Position: Senior MS Fabric Data Engineer – Azure

Location: St. Louis, MO – Fully Onsite

Experience: Financial or Banking sector experience is mandatory

Job Summary

We are seeking a highly experienced Senior MS Fabric Data Engineer with deep expertise in Microsoft data services, including Microsoft Fabric, Azure Data Factory, Azure Synapse, and ETL/ELT processes.

The ideal candidate will be responsible for designing, developing, modernizing, and maintaining cloud-based data pipelines and scalable data solutions to support analytics, reporting, and business intelligence capabilities.

Key Responsibilities

• Lead modernization of legacy data platforms, including migration of ETL/ELT and data ingestion frameworks to cloud platforms such as Azure and AWS.
• Own end-to-end data solution architecture, ensuring scalability, security, performance, and alignment with business objectives.
• Provide technical leadership, mentor engineering teams, and enforce data engineering best practices.
• Drive decision-making in ambiguous environments while proactively identifying and mitigating risks, dependencies, and constraints.
• Implement data governance, security, privacy, and compliance frameworks, including PII and regulatory standards.
• Collaborate with business stakeholders, analytics teams, and technology partners to translate business needs into scalable data solutions.
• Architect and integrate data from multiple sources into high-performing cloud data platforms.
• Design, develop, and optimize ETL/ELT pipelines using Azure Data Factory, Databricks, Spark, SSIS, and related technologies.
• Partner with analytics and BI teams to support reporting, dashboards, and advanced analytics use cases.
• Ensure data quality through profiling, validation, monitoring, reconciliation, and issue resolution processes.
• Establish CI/CD and DevOps practices for data engineering workflows using tools such as Azure DevOps, Git, or Jenkins.
• Monitor and optimize pipeline performance, scalability, reliability, and cost efficiency.
• Lead unit testing, system testing, integration testing, and maintain comprehensive technical documentation.
• Drive continuous improvement and innovation across tools, frameworks, processes, and data architecture.

Required Skills and Qualifications

• 12+ years of experience designing and implementing data warehouse, data engineering, and analytics solutions across on-premises and cloud environments.
• Strong expertise in data warehousing concepts, including ETL/ELT, data quality management, privacy, security, and master data management.
• Hands-on experience with Azure Data Factory, SSIS, Data Factory, Microsoft Fabric, Fabric Lakehouse, Azure Synapse, and related Microsoft data services.
• Experience with cloud-native data lakes, lakehouses, and data warehouses.
• Strong programming experience in Python, Scala, or Java for distributed data processing and analytics using Spark.
• Experience with CI/CD practices and tools such as Azure DevOps, Git, Jenkins, or similar platforms.
• Prior experience in the financial services or banking sector is mandatory.