Microsoft Fabric Engineer
NTT DATA North America · Irving, TX · Today
HybridInformation Technology$30/hrOther
About the role
In this role, you will be responsible for the end-to-end engineering and operational support of Microsoft Fabric, a cornerstone platform driving enterprise data strategy and analytics capabilities. The platform integrates core services such as data ingestion, transformation, semantic modeling, and reporting within a unified architecture.
Responsibilities
- Lead complex initiatives to design and enhance enterprise data platform capabilities within Microsoft Fabric, supporting business-critical analytics workloads
- Participate in strategic efforts to expand Fabric adoption, onboard new use cases, and improve platform scalability and performance
- Evaluate internal and external data, analytics, and integration solutions to align with target-state architecture and enterprise data strategy
- Review and analyze high-impact incidents related to data pipelines, platform performance, or data quality; implement preventative controls and resiliency improvements
- Design, build, deploy, and maintain Fabric solutions including data ingestion pipelines, transformations, semantic models, and reporting layers
- Develop and optimize data pipelines and orchestration workflows to improve performance, reliability, and cost efficiency
- Implement infrastructure-as-code (IaC) and automation to enable repeatable deployment of Fabric components and supporting services
- Contribute to Agile development practices by designing, testing, debugging, and documenting data engineering and platform solutions
- Make technical decisions on architecture design, integration patterns, and data modeling approaches, while identifying risks and resource requirements
- Manage and support production operations, including monitoring, performance tuning, troubleshooting, and incident response for Fabric workloads
- Enforce enterprise data governance, security, and compliance standards (e.g., RBAC, data lineage, sensitivity labels, and access controls)
- Drive data platform integration across systems, including cloud services, data sources, and downstream applications
- Recommend solutions to optimize platform performance, cost, and scalability while improving data quality and operational efficiency
- Collaborate with data engineering, analytics, cybersecurity, and platform teams to resolve issues and deliver secure, high-quality data solutions
- Interact with internal customers, business stakeholders, and technology vendors (including Microsoft) to deliver and support analytics capabilities
Requirements
- 5+ years of experience in data engineering, data platforms, or analytics engineering
- Hands-on experience with Microsoft Fabric, or closely related technologies (Power BI, Azure Data Factory, Synapse Analytics)
- Strong experience designing and supporting data pipelines, ETL/ELT processes, and data integration workflows
- Proficiency in infrastructure-as-code (e.g., Terraform) and CI/CD practices for data platforms
- Strong understanding of data governance principles, including data lineage, access control, and compliance
- Able to work in regulated environments with strict security, risk, and compliance requirements
- Strong collaboration and problem-solving skills across cross-functional teams
Qualifications
- Experience with Microsoft Fabric-specific services (Lakehouse, Data Factory, OneLake, Semantic Models, Real-Time Analytics)
- Experience with enterprise data governance tools (e.g., Microsoft Purview, data cataloging, DLP policies)
- Familiarity with multi-cloud data and analytics ecosystems (Azure, GCP)
- Experience with pipeline optimization, cost management, and performance engineering at scale
- Understanding of DevSecOps practices and secure data platform design
- Knowledge of regulatory and compliance requirements in financial services (data privacy, audit, risk controls)
- Experience integrating Fabric with enterprise identity and access management solutions
- Microsoft certifications related to Fabric, Azure Data Engineering, or Analytics