Data Analytics Engineer

Shaw Industries • Dalton, GA

1d • Hybrid

About The Position

Shaw Industries Group, Inc. is seeking a Data Analytics Engineer to join its Residential Enablement and Insights team in Dalton, Georgia. The role operates in a hybrid work environment, with 1–3 days in Dalton, GA. It sits at the intersection of business strategy, advanced analytics, and data engineering, emphasizing data modeling and Databricks.

The Analytics Engineer designs and implements scalable, trusted data models for visualization tools that support strategic decisions across Residential Sales and Marketing. The role helps enable data self-service and modern analytics practices by turning business requirements into analytics solutions, building data pipelines, and promoting reliable, well-documented data assets. The position collaborates with business stakeholders, Data Engineering, and other cross-functional teams to ensure data quality, integrity, performance, and governance. Shaw Industries is an equal opportunity employer as to all protected groups, including protected veterans and individuals with disabilities.

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.
• Strong communication skills and 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.
• Passion for creating clean, reusable, and well-documented data assets.

Nice To Haves

• 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, preferably in a cloud environment such as Azure, using notebooks and modern storage formats such as Delta Lake to process, transform, and model data.
• 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.
• 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.
• Interest in continuous learning, especially in machine learning, AI, and advanced analytics.

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 such as 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.
• Contribute to team learning, documentation, and adoption of analytics best practices; share knowledge and support the development of others.
• Document, standardize, and continuously improve 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level