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# Business Intelligence & Data Engineer

- **Company:** Versalytix, Inc.
- **Location:** Maryville, TN, United States
- **Experience:** Expert
- **Salary:** $98,500.0 - $105,500.0
- **Contract:** Permanent contract
- **Skills:** Code Review, Continuous Integration, Data Validation, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Warehousing, Dimensional Modeling, Python (Programming Language), Performance Tuning, Query Optimization, Tensorflow, SQL Databases, SQL Server Integration Services, Transact-SQL, Management of Software Versions, Data Ingestion, Azure Data Factory, Apache Spark, Git, Pandas, Microsoft Fabric, Information Technology, HuggingFace, Software Version Control, Data Pipelines
- **Published:** September 22, 2026
- **Apply:** https://www.versalytix.com/jobs/senior-business-intelligence-data-engineer

## About the Role

Work Authorization: Must be authorized to work in the U.S. without current or future sponsorship, + 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:
o Complex joins
o window functions
o 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:
o Layered architectures (raw, curated, consumption)

 + ELT patterns
 + Batch and incremental loading strategies
 + 3+ years of hands-on dimensional modeling, including:
o Star and snowflake schemas
o Fact and dimension table design
o Surrogate keys and SCD Type 1/2

 + 1+ years developing transformations in notebooks
 + Working knowledge of how analysts and business users consume data, including:
o Gathering requirements
o Visual performance considerations
o 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, + 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

## Description

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., + 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:
o Data quality checks and validation
o Reproducibility: parameterization, modular notebooks, and version control
o 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.


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