About the Role
Our client is looking for a Senior Business Intelligence & Data Engineer to connect traditional BI engineering with modern cloud analytics. On the traditional side, that means T-SQL and ETL, with SSIS a plus. On the modern side, it means scalable data pipelines into Microsoft Fabric and transformations built in notebooks using Python and Pandas.
The role focuses on:
Data ingestion
Data modeling
Transformations
Getting the semantic layer ready for analytics
You won't build production reports. You will need to understand reporting needs well enough to design data and semantic models that support analytics and self-service BI.
Job Details
Location: Maryville, TN. 100% in-office; no remote or hybrid option.
Compensation: $98,500 – $105,500 base salary
Incentives: Eligible for a cash incentive bonus (10% target of base salary), a one-time equity grant of $5,000, and product discounts
Work Authorization: Must be authorized to work in the U.S. without current or future sponsorship
What You'll Do
Design and implement ingestion pipelines that move data from source systems into Microsoft Fabric (Lakehouse/Warehouse). Sources include SQL databases, files, APIs, and SaaS applications.
Build and maintain pipelines using Azure Data Factory (ADF) and/or Fabric-native orchestration.
Build transformation logic in notebooks using Python, Pandas, and Spark where applicable.
Apply best practices in three areas:
Data quality checks and validation
Reproducibility: parameterization, modular notebooks, and version control
Performance optimization: partitioning, pushdown, and caching strategies
Design and maintain enterprise data warehouse models.
Prepare data for semantic models and analytics use. Work with report developers and analysts to make sure models match how the business actually uses BI.
Work with analysts, application teams, and data owners to turn requirements into scalable pipelines and models.
Take part in code reviews, documentation, and handoffs to operations.
Help set standards for naming, versioning, environments, and deployment.
What You Bring
3+ years of professional experience in BI, data engineering, or data warehouse development in an enterprise environment
2+ years of hands-on T-SQL, including:
Complex joins
window functions
CTEs
Query optimization and performance tuning
Building transformation logic in SQL
2+ years designing and implementing ETL/ELT pipelines
1+ years building pipelines with Azure Data Factory or a comparable orchestration tool
3+ years applying modern data warehousing principles, including:
Layered architectures (raw, curated, consumption)
ELT patterns
Batch and incremental loading strategies
3+ years of hands-on dimensional modeling, including:
Star and snowflake schemas
Fact and dimension table design
Surrogate keys and SCD Type 1/2
1+ years developing transformations in notebooks
Working knowledge of how analysts and business users consume data, including:
Gathering requirements
Visual performance considerations
Data shaping
Strong verbal and written communication skills, and a collaborative approach
Ability to manage your own workload, meet tight deadlines, and work independently with minimal supervision
A bachelor's degree in Computer Science, Engineering, or a related field is preferred
Nice to Have
Microsoft Fabric experience: Lakehouse, Warehouse, pipelines, notebooks, and shortcuts
Power BI semantic models and tabular modeling concepts
SSIS
Data governance, cataloging, and lineage practices
CI/CD for data assets: Git integration and environment promotion
TensorFlow, PyTorch, or Hugging Face
Work Environment
Professional office environment
Occasional physical activity, including bending, kneeling, squatting, standing, walking, reaching (including overhead), and fine motor tasks
About the company
Versalytix is conducting this search on behalf of our client, an established U.S. manufacturer. Our client is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or protected veteran status.