Join a Fortune 100 enterprise in Nashville where Applix Inc. empowers you to drive enterprise wide adoption of Microsoft Fabric through a centralized BI and Intelligent Automation COE. This on-site, full-time role offers a collaborative culture, strong growth potential, and comprehensive benefits including 401(k), health, dental, and vision coverage. You will work closely with business units and engineering teams to design scalable data architectures, migrate legacy analytics to Fabric, and shape lakehouse governance and semantic models, all while maintaining high performance and data quality.
Responsibilities
- Operate within a centralized BI and Intelligent Automation COE to enable enterprise wide adoption of Microsoft Fabric and modern analytics practices.
- Collaborate with business units and engineering teams to design scalable data architectures, develop reusable assets, and guide the migration of legacy analytics environments to Fabric.
- Contribute to shaping Lakehouse architectures, semantic models, and governance frameworks to ensure reliability, performance, and data quality across the analytics ecosystem.
Requirements
- Strong experience in data engineering, data modeling, and modern analytics platforms
- Hands-on expertise with Microsoft Fabric, including Lakehouse, Data Factory (pipelines, Dataflows Gen2), and notebooks
- Advanced proficiency in Power BI, including semantic modeling, DAX, performance tuning, and workspace design
- Solid understanding of ETL/ELT processes, medallion architecture (Bronze/Silver/Gold), and SQL-based transformations
- Experience building scalable data pipelines, reusable data assets, and governed analytics environments
- Strong troubleshooting skills across data pipelines, BI tools, and distributed data systems
- Experience with scripting or automation using Python, PowerShell, or SQL
- Ability to collaborate with cross-functional teams and communicate effectively with both technical and business stakeholders
- Experience in enterprise environments or COE/platform enablement roles is a strong plus
- Familiarity with Azure data services, CI/CD practices, and BI platform governance is preferred
- Education: Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field
Technologies
- Microsoft Fabric, Lakehouse, Data Factory, Dataflows Gen2, Notebooks
- Power BI, DAX, SQL
- Python, PowerShell
- Azure Data Lake Storage (ADLS), Azure Synapse Analytics, Azure SQL
- Medallion architecture (Bronze/Silver/Gold)
Benefits
- 401(k)
- Dental insurance
- Health insurance
- Vision insurance
Role details
Role: Senior Data & Analytics Engineer – Microsoft Fabric (COE) for a full-time, on-site engagement in Nashville, TN. You will be part of a centralized BI and Intelligent Automation COE, focusing on enterprise wide Fabric adoption and modern analytics practices. Your work centers on partnering with business units and engineering teams to design scalable data architectures, create reusable assets, and guide the migration of legacy analytics environments to Fabric, while helping shape Lakehouse architectures, semantic models, and governance frameworks.
Compensation and location
Salary: $70,000 - $110,000 per year
Location: Nashville, TN (onsite)
Application questions
- Do you have a green card or are you a US Citizen?
- Total years of experience in data engineering / analytics?
- Years of experience with Power BI?
- Are you willing to work on-site in Nashville, TN or Dallas, TX or Peoria IL?
- Years of experience working with Delta tables / Lakehouse architectures?
- Rate your DAX proficiency (1–10)
- Years of experience with SQL for data transformation and analysis?
- Years of experience with Azure data services (ADLS, Synapse, Azure SQL, etc.)?
- Have you built or supported a Fabric Lakehouse environment?
- Have you created Data Factory pipelines in Fabric?
- Have you worked with Dataflows Gen2?
- Have you implemented medallion architecture (Bronze/Silver/Gold)?
- Have you built and optimized Power BI semantic models at scale?
- Have you performed Power BI performance tuning (dataset optimization, query reduction, etc.)?
- Do you have experience with Python, PowerShell, or scripting for automation?
