Data Analytics Engineer

Shaw Industries • Dalton, GA

2d • Hybrid

About The Position

Shaw Industries Group, Inc. is seeking an Analytics Engineer to join its Residential Enablement and Insights team in Dalton, Georgia. The company develops flooring and other surface solutions for residential, commercial, and outdoor environments and has more than 18,000 associates worldwide.

This role operates at the intersection of business strategy, advanced analytics, and data engineering, with an emphasis on data modeling and Databricks. The Analytics Engineer will design and implement scalable, trusted data models for visualization tools that support strategic decision-making across Residential Sales and Marketing. The role also supports data self-service and modern analytics practices across Shaw. The position has a hybrid work environment with 1–3 days in Dalton, Georgia.

The role involves partnering with business stakeholders to define requirements; building data models, pipelines, and analytics-ready datasets; and collaborating with Data Engineering and cross-functional teams on data quality, governance, and performance. It also contributes to documentation, team learning, adoption of analytics best practices, and continuous improvement of data assets and processes.

Requirements

• Experience using SQL to query, transform, and analyze data.
• Familiarity with designing logical and physical data models that support scalable analytics.
• Bachelor’s degree in computer science, Data Analytics, Information Systems, Business, or a related field.
• Experience building reports and dashboards in Power BI, including DAX, Power Query, dataflows, and data security concepts such as row-level security.
• Some experience with Databricks to process, transform, and model data using notebooks and modern storage formats such as Delta Lake.
• Understanding of data pipeline concepts, including ETL/ELT processes, orchestration, and data lake architectures such as Azure Data Lake.
• Familiarity with Python or R for data transformation, automation, and analytical tasks.
• Some experience with version control systems such as Git and familiarity with collaborative development practices such as DataOps or CI/CD.
• Strong communication skills and the ability to explain complex technical concepts in business context.
• Excellent problem-solving and analytical thinking skills.
• Ability to work cross-functionally in a highly collaborative environment.
• Interest in continuous learning, particularly in machine learning, AI, and advanced analytics.
• Passion for creating clean, reusable, and well-documented data assets.

Nice To Haves

• Experience delivering modern analytics solutions using Power BI, Databricks, and data modeling practices.
• Experience with Power BI, Git, and Azure/Data Lake.
• Experience working in or supporting business analytics teams within a large enterprise environment.
• Databricks experience in a cloud environment such as Azure.

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 semantic layers, star schemas, and data marts for reliable, scalable self-service analytics.
• Build and maintain data pipelines using modern data platforms such as Databricks, transforming raw and complex data into analytics-ready datasets.
• Collaborate with Data Engineering and cross-functional teams to support data quality, integrity, performance, and data governance standards.
• Apply and promote best practices in data modeling, analytics engineering, and dashboard design.
• Contribute to team learning, documentation, and adoption of analytics best practices.
• Document, standardize, and continuously improve data assets, including models, datasets, and metadata.
• Expand knowledge of analytics tools, technologies, and data architecture and apply new capabilities to improve solutions and processes.

What This Job Offers

• Job Type: Full-time