Senior Analytics Engineer

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 18,000 associates worldwide.

Job Overview

We are seeking an experienced Analytics Engineer III 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.

Key Responsibilities:

• Partner with senior business leaders (DVPs, VPs, Directors) to gather requirements and translate them into scalable data models and analytic frameworks.
• Design, develop, and maintain semantic models, star schemas, and data marts to support self-service analytics.
• Build and deploy advanced analytic pipelines using Databricks, transforming large and complex data sets into analytics-ready assets.
• Create clear, actionable visualizations and dashboards using Power BI, enabling users to uncover insights and make informed decisions.
• Collaborate with Data Engineering to ensure data integrity, optimize pipeline performance, and enforce data governance standards.
• Provide subject matter expertise in Power BI development, data modeling practices, and dashboard UX.
• Coach and mentor analysts and business users in best practices for data visualization, model reuse, and analytic thinking.
• Contribute to the development of enterprise data standards, catalogs, and metadata documentation.
• Stay current with evolving technologies in analytics, cloud computing, and data engineering — especially Databricks, Power BI, and modern data architectures.

Requirements

Technical Skills & Experience:

• Advanced knowledge of SQL and experience designing scalable logical and physical data models.
• Expert-level proficiency in Power BI (DAX, Power Query, dataflows, custom visuals, row-level security).
• Proven experience working with Databricks (preferably on Azure) to process and model data using notebooks and Delta Lake.
• Strong understanding of data pipeline orchestration, ETL, and data lake architectures (Azure Data Lake).
• Familiarity with Python or R for advanced analytics and automation tasks.
• Experience working with version control (e.g., Git) and implementing DataOps or CI/CD practices.

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.

Qualifications:

• Bachelor’s degree in Computer Science, Data Analytics, Information Systems, Business, or a related field.
• 2–5+ years of experience delivering modern analytics solutions using Power BI, Databricks, and strong data modeling practices.
• Experience working in or supporting business analytics teams within a large enterprise environment.
• Proven experience designing and implementing large-scale big data systems using Hadoop, Spark, Apache Hive, or similar frameworks.
• Strong proficiency in SQL databases such as Microsoft SQL Server, Oracle, and cloud databases including Azure Data Lake or similar platforms.
• Extensive knowledge of data warehousing design principles including dimensional modeling and ETL pipeline development.
• Hands-on experience with cloud-based data management solutions on AWS or other public cloud providers.
• Proficiency in software development languages such as Java and Python for building scalable analytics applications.
• Familiarity with business intelligence tools like Looker for creating insightful dashboards and reports.
• Knowledge of data modeling techniques including linked data concepts to enhance data integration across diverse sources.
• Experience working within Agile development environments with tools like Talend for ETL workflows.
• Strong analysis skills combined with expertise in database design, query management, shell scripting (Bash/Unix), VBA, and RESTful API integration.

Join us to be at the forefront of transforming raw data into actionable insights that drive strategic growth!

This position operates in a hybrid work environment. Looking for candidates that are already local/within 100 miles of driving distance of Dalton, GA.