Business Intelligence Engineer

Briggs Industrial Solutions•Dallas, TX

7d•Hybrid

About The Position

The Business Intelligence Engineer strengthens the data foundation that supports decision-making across Sammons Industrial’s businesses. Working primarily in Microsoft Fabric, this hands-on role owns and improves data pipelines, transformations, and structures that turn raw information into reliable, actionable insights. The engineer works independently and partners with IT, Reporting & Analytics, and business teams to support analytics, automation, and AI capabilities. The position is based at the company’s Dallas, Texas corporate office and follows a hybrid schedule each week. The role may require responding to early-morning alerts to keep critical data moving.

Requirements

3–5 years of experience in data engineering, BI engineering, or a related field.
Hands-on experience independently building, troubleshooting, and managing production data solutions.
Practical experience with Microsoft Fabric pipelines, notebooks, Lakehouse, Warehouse, OneLake, and medallion architecture, including independent ownership of Bronze and Silver layers.
Advanced SQL skills and working proficiency in Python.
Experience with data transformations, dimensional modeling, Power BI, and Git-based source control or DevOps practices.
Ability to take ownership, pay attention to detail, communicate clearly, build durable solutions, and work independently while collaborating with others.

Nice To Haves

Experience with Spark/PySpark, CI/CD, or AI-enabled data solutions.

Responsibilities

Design, build, and maintain Microsoft Fabric pipelines, notebooks, Lakehouse and Warehouse solutions, and Bronze and Silver data layers using medallion architecture.
Use SQL, Python, and dimensional modeling to transform data, improve performance, and support Power BI semantic models and Gold-layer data products in partnership with Reporting & Analytics.
Monitor data processes, investigate issues, resolve root causes, and maintain dependable solutions through testing, documentation, source control, and DevOps practices.
Respond to early-morning alerts when needed to keep critical data moving.
Partner with IT, Reporting & Analytics, and business teams to improve data quality and engineering practices, and prepare trusted data for advanced analytics, automation, and AI.