Data Science Engineer

Company Description

Cornerstone Building Brands is a leading manufacturer of exterior building products for residential and low-rise non-residential buildings in North America. Headquartered in Cary, N.C., we serve residential and commercial customers across the new construction and Repair & Remodel (R&R) markets. Our market-leading portfolio of products spans vinyl windows, vinyl siding, stone veneer, metal roofing, metal wall systems and metal accessories. Cornerstone Building Brands’ broad, multi-channel distribution platform and expansive national footprint includes more than 18,800 team members at manufacturing, distribution and office locations throughout North America. Corporate stewardship and Environmental, Social and Governance (ESG) responsibility are embedded in our culture. We are committed to contributing positively to the communities where we live, work and play. For more information, visit us at cornerstonebuildingbrands.com

Job Description

The Data Science Engineer – Business Intelligence, Analytics & AI transforms enterprise data into actionable insights by designing, developing, and delivering scalable analytics solutions. This role partners with business stakeholders, leadership, data engineering, and technology teams to create trusted data products, optimize reporting processes, and deliver executive-ready analytics that support strategic decision-making, operational efficiency, and measurable business value.

KEY RESPONSIBILITIES:

Business Intelligence & Analytics Development

• Design, develop, and maintain Power BI dashboards, reports, scorecards, KPI frameworks, semantic models, datasets, and reusable business metrics that support enterprise reporting and decision-making.
• Translate business requirements into scalable, user-friendly analytics solutions with strong visual storytelling, performance, usability, and adoption.
• Deliver executive-ready analytics that clearly communicate insights to technical and non-technical audiences and drive measurable business outcomes.

Data Modeling & Data Engineering

• Design and maintain dimensional data models, including star and snowflake schemas, aligned with enterprise architecture and modeling standards.
• Develop and support scalable ETL/ELT processes, analytical data pipelines, and integrations across enterprise systems.
• Partner with Data Engineering teams to improve data availability, reliability, performance, and reporting readiness.

Data Quality, Governance & Testing

• Ensure data accuracy, completeness, consistency, integrity, and compliance with enterprise governance, security, privacy, and quality standards.
• Perform validation, reconciliation, root cause analysis, troubleshooting, and testing across unit, integration, regression, and user acceptance activities.
• Document business rules, data definitions, lineage, calculation logic, and testing outcomes to support trusted analytics delivery.

Business Partnership & Requirements Management

• Partner with stakeholders to understand business processes, reporting needs, strategic objectives, and opportunities for analytics and AI-enabled improvement.
• Facilitate requirements gathering, translate needs into technical specifications, and lead solution reviews, demos, UAT, and stakeholder training.
• Serve as a trusted advisor by providing data-driven recommendations that improve business performance and operational efficiency.

Continuous Improvement & Innovation

• Identify opportunities to automate manual processes, improve operational efficiency, and promote self-service analytics adoption.
• Evaluate and implement emerging analytics technologies, AI-enabled capabilities, standards, reusable assets, and analytics accelerators.
• Contribute to a culture of innovation, continuous learning, collaboration, and data-driven decision-making.

AI-Augmented Data Science Responsibilities

• Design AI-powered analytics workflows using prompt engineering for BI, reporting, data exploration, automation, and decision-support use cases.
• Leverage Snowflake Cortex Analyst, Power BI Copilot, Microsoft Copilot, GitHub Copilot, and other LLM-based tools to accelerate analytics delivery and improve outcomes.
• Develop and govern AI-ready semantic models, business metrics, data abstractions, and trusted semantic layers that support traditional BI and natural language analytics.
• Design and support AI agents, agentic analytics solutions, MCP/API integrations, and LLM-powered workflows that securely connect governed enterprise data sources.
• Evaluate, validate, and monitor AI-generated insights for accuracy, reliability, compliance, business relevance, and responsible AI adoption.

Qualifications

QUALIFICATIONS AND PROFESSIONAL EXPERIENCE 

Required

• College degree in Computer Science, Information Systems, Data Science, Statistics, Industrial Engineering, or a related field.
• 2+ years of experience in Business Intelligence, Data Analytics, Data Engineering, or related disciplines, including enterprise Power BI solution development.
• Experience designing analytical data models, reporting solutions, semantic models, and scalable BI assets.
• Experience gathering business requirements, partnering with stakeholders, and translating needs into technical solutions.
• Experience supporting testing, deployment, troubleshooting, data validation, and production support activities.

Preferred

• Experience with cloud analytics platforms such as Snowflake, Microsoft Fabric, Azure Synapse Analytics, Databricks, or similar technologies.
• Experience operating in Agile/Scrum environments and supporting enterprise-scale reporting and analytics initiatives.
• Hands-on experience using LLM-based tools in data, analytics, BI, or software engineering environments, including GitHub Copilot, Microsoft Copilot, Power BI Copilot, Snowflake Cortex Analyst, Claude, ChatGPT Enterprise, or similar platforms.
• Experience designing prompts, semantic models, and natural language analytics experiences for AI-powered reporting and self-service analytics.
• Familiarity with AI agents, conversational analytics, LLM workflows, responsible AI principles, AI governance, AI security, and validation of AI-generated outputs.

Additional Information

Work from home! (Flexibility to go to the office once per month)

Why work for Cornerstone Building Brands?

Our teams are at the heart of our purpose to positively contribute to the communities where we live, work and play.

Full-time 
Schedule: monday to friday 8am to 5pm 
Team members receive medical, dental and vision benefits starting day 1.
Other benefits include paid holidays, life insurance, LTD, STD, trainings, and professional development. You can also join one of our Employee Resource Groups which help support our commitment to providing a diverse and inclusive work environment.
Free virtual English course
Employee Assistance Program