Analytics Engineer

Shaw Industries•Dalton, GA

1d•Hybrid

About The Position

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, Power BI, and Databricks. As an Analytics Engineer, you will design and implement scalable, trusted data models and 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. This position operates in a hybrid work environment with 1 - 3 days in Dalton, GA.

Requirements

Experience using SQL to query, transform, and analyze data, and familiarity with designing logical and physical data models that support scalable analytics.
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.
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.
Bachelor’s degree in Computer Science, Data Analytics, Information Systems, Business, or a related field.
Experience delivering modern analytics solutions using Power BI, Databricks, and data modeling practices OR applicable college course work

Nice To Haves

Experience working in or supporting business analytics teams within a large enterprise environment.

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.
Develop clear, actionable visualizations and dashboards (e.g., Power BI) that enable users to explore data, uncover insights, and drive informed decisions.
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.