Senior Data Engineer

• Design, develop, and maintain scalable ETL/ELT pipelines utilizing Microsoft Fabric, Azure Data Factory, Dataflows, and other Azure services.
• Build and support enterprise data integration solutions connecting internal and external systems, APIs, SaaS platforms, databases, and third-party applications.
• Design and implement Microsoft Fabric Lakehouse, Warehouse, and OneLake solutions following best practices.
• Develop and optimize SQL-based data transformations, stored procedures, views, and performance-tuned datasets.
• Create reusable and scalable ingestion frameworks supporting batch and near real-time data processing.
• Monitor and troubleshoot data pipelines to ensure high reliability, performance, and operational stability.

Data Architecture & Modeling

• Collaborate with Data Architects to design enterprise data models supporting analytics, operational reporting, and self-service BI.
• Implement and support Medallion Architecture (Bronze, Silver, Gold layers) within Microsoft Fabric.
• Define dimensional models, star schemas, fact tables, dimension tables, and semantic modeling structures for analytics consumption.
• Recommend architectural improvements that increase scalability, maintainability, and performance.

Microsoft Fabric & Azure Platform

• Develop solutions utilizing:
• Microsoft Fabric
• OneLake
• Lakehouse
• Warehouse
• Data Factory
• Pipelines
• Semantic Models
• Power BI
• Work with Azure services to support secure data movement, storage, integration, and processing workloads.
• Participate in environment configuration, deployment planning, and operational support activities.

Data Governance & Quality

• Implement automated data quality validation, reconciliation, and exception handling processes.
• Support data governance initiatives including:
• Metadata management
• Data lineage
• Data stewardship
• Data cataloging
• Data classification
• Establish monitoring and alerting processes for pipeline failures, schema drift, and data anomalies.
• Promote data standards and governance best practices across engineering initiatives.

DevOps & Automation

• Implement CI/CD deployment processes using Azure DevOps and Git repositories.
• Create automated deployment pipelines for Fabric artifacts and data engineering solutions.
• Support source control, pull request workflows, branching strategies, release management, and deployment automation.
• Develop Infrastructure-as-Code and configuration management patterns where appropriate.

Security & Compliance

• Implement data security controls, access management, encryption, and auditing capabilities.
• Ensure compliance with internal governance policies and industry best practices.
• Support regulatory and privacy requirements related to sensitive business and employee data.

Collaboration & Leadership

• Partner with business stakeholders, analysts, architects, and application teams to understand data requirements.
• Mentor junior engineers and promote engineering best practices.
• Participate in technology evaluations and recommend new tools, frameworks, and architectural improvements.

Contribute to enterprise standards for Microsoft Fabric, data engineering, and analytics delivery.

Loyal Source is seeking a highly skilled Senior Data Engineer to design, build, and support scalable enterprise data platforms using Microsoft Fabric, Azure Data Services, and modern data engineering practices.

This role will be responsible for developing robust data pipelines, designing data models, implementing governance and data quality controls, and enabling analytics and reporting solutions across the organization. The ideal candidate combines strong technical engineering skills with the ability to collaborate with business stakeholders, architects, analysts, and application teams to deliver trusted and governed data products.

The Senior Data Engineer will play a key role in advancing Loyal Source’s enterprise analytics strategy through Microsoft Fabric, Azure DevOps, Power BI, Salesforce, Workday, and other enterprise platforms., * Bachelor’s Degree in Computer Science, Data Engineering, Information Systems, Mathematics, Software Engineering, or related discipline.

• 5+ years of hands-on experience in Data Engineering, Data Platform Engineering, Data Warehousing, or Analytics Engineering.
• Advanced SQL development skills, including query optimization and performance tuning.
• Strong Python development experience for data processing, integrations, automation, and orchestration.
• Experience designing and implementing enterprise data warehouses and analytical data platforms.
• Experience building enterprise ETL/ELT solutions using:
• Microsoft Fabric
• Azure Data Factory
• Azure Synapse Analytics
• SSIS or comparable technologies
• Hands-on experience with:
• Data Lakes
• Lakehouses
• Data Warehouses
• Dimensional Modeling
• Star Schema Design
• Experience integrating data from APIs, SaaS platforms, databases, and external systems.
• Experience with source control and Git-based development practices., * Microsoft Fabric implementation experience in production environments.
• Experience with:

o OneLake

o Data Factory

o Lakehouse

o Warehouse

o Semantic Models

o Power BI

• Experience with Azure DevOps and CI/CD deployment pipelines.
• Experience with Delta Lake and modern lakehouse architectures.
• Experience developing REST APIs, microservices, and backend integrations.
• Experience supporting enterprise reporting and analytics initiatives.
• Experience with Salesforce and Workday data models and integrations.
• Familiarity with healthcare, workforce management, staffing, government contracting, or enterprise operational reporting.
• Microsoft Azure and/or Microsoft Fabric certifications., * Microsoft Fabric
• Azure Data Factory
• SQL
• Python
• Azure Cloud Services
• Data Warehousing
• Data Modeling
• ETL / ELT
• Git
• Azure DevOps

Preferred

• Power BI
• Delta Lake
• OneLake
• Lakehouse Architecture
• REST APIs
• Azure Functions
• Salesforce
• Workday
• Synapse Analytics