Data Analytics Engineer

Job Title

Position Overview

Shaw Industries Group Inc. is a leader in flooring and other surface solutions designed for residential housing commercial spaces and outdoor environments. Leveraging strengths in design innovation and operational excellence the company takes a people-centered customer-focused and growth-minded approach to meet diverse market needs. It creates differentiated customer experiences through its expansive portfolio of brands: Anderson Tuftex COREtec Shaw Floors Patcraft Philadelphia Commercial Shaw Contract Shaw Sports Turf Shawgrass Southwest Greens Watershed Geo and more. Headquartered in Dalton Georgia Shaw is a wholly owned subsidiary of Berkshire Hathaway Inc. with more than $6 billion in annual sales and 18000 associates worldwide.

Location: Dalton GA

This position operates in a hybrid work environment with 1 - 3 days in Dalton GA.

Shaw Industries is seeking an Analytics Engineer to join our Residential Enablement and Insights team in Dalton GA. This role sits at the intersection of business strategy advanced analytics and data engineering with a strong emphasis on data modeling and Databricks. As an Analytics Engineer you will design and implement scalable trusted data models for use in visualization tools that drive strategic decision-making across our Residential Sales and Marketing organizations. The ideal candidate will blend technical depth with business insight playing a critical role in enabling data self-service and modern analytics practices across Shaw.

Key Responsibilities:

• Partner with business stakeholders to gather requirements and translate them into scalable data models and analytic solutions that support decision-making.
• Design develop and maintain data models including semantic layers star schemas and data marts to enable reliable and scalable self-service analytics.
• Build and maintain data pipelines using modern data platforms (e.g. Databricks) transforming raw and complex data into analytics-ready datasets.
• Collaborate with Data Engineering and cross-functional teams to ensure data quality integrity and performance and to support adherence to data governance standards.
• Apply and promote best practices in data modeling analytics engineering and dashboard design contributing to consistent and effective data solutions.
• Share knowledge and support the development of others by contributing to team learning documentation and adoption of analytics best practices.
• Contribute to the documentation standardization and ongoing improvement of data assets including data models datasets and metadata.
• Continuously expand knowledge of analytics tools technologies and data architecture and apply new capabilities to improve solutions and processes.

Technical Skills & Experience:

• Experience building reports and dashboards in Power BI including working with capabilities such as DAX Power Query dataflows and data security concepts (e.g. row-level security).
• Some experience working with Databricks (preferably in a cloud environment such as Azure) to process transform and model data using notebooks and modern storage formats (e.g. Delta Lake).
• Understanding of data pipeline concepts including ETL/ELT processes orchestration and data lake architectures (e.g. Azure Data Lake).
• Familiarity with programming languages such as Python or R for data transformation automation and analytical tasks.
• Some experience working with version control systems (e.g. Git) and familiarity with collaborative development practices such as DataOps or CI/CD.

Required Qualifications:

• Experience using SQL to query transform and analyze data and familiarity with designing logical and physical data models that support scalable analytics.
• Bachelors degree in computer science Data Analytics Information Systems Business or a related field.

Strongly preferred:

• Experience delivering modern analytics solutions using Power BI Databricks and data modeling practices.
• Experience in PowerBI GIT Azure/Data Lake
• Experience working in or supporting business analytics teams within a large enterprise environment.

Core Competencies:

• Strong communication skills with the ability to translate complex technical concepts into business context.
• Excellent problem-solving and analytical thinking skills.
• Ability to work cross-functionally in a highly collaborative environment.
• Interest in continuous learning especially in areas of machine learning AI and advanced analytics.
• Passion for creating clean reusable and well-documented data assets.

Work Shift