IT Data Science Principal, Data Warehouse

Cornerstone Building Brands

. Develop enterprise analytics and AI roadmaps aligned with business strategy, value, and feasibility .

Posted 10/26/2026full-timeRemote • North Carolina • United StatesLead💰 $120,000 - $140,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing enterprise analytics and AI roadmaps, leading cross-functional teams, and implementing scalable data solutions. Proficient in managing data governance, dimensional modeling, and delivering AI/ML solutions in production environments.

Highest-signal resume keywords

Enterprise Analytics DevelopmentAI Solutions DeliverySnowflake Platform ExpertiseDimensional ModelingData Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalyticsMachine LearningETL/ELT DevelopmentSQL EngineeringDimensional ModelingData GovernanceMLOps PracticesCloud Data WarehousingData Lineage ManagementKPI Design

Soft Skills

People LeadershipStakeholder ManagementCoachingCommunicationPrioritization

Tools & Technologies

SnowflakeSSISODIMatillionCortex AnalystAgile MethodologiesDevOps PracticesGenAI ToolingBI ToolsData Warehouse Frameworks

Industry Keywords

Manufacturing DomainData QualityMaster Data ManagementResponsible AIMedallion Architecture

Tech Stack

Tools & technologies

CloudERPETLMatillionSnowflakeSQLSSISVault

About the role

Key responsibilities & impact

Develop enterprise analytics and AI roadmaps aligned with business strategy, value, and feasibility
Establish prioritization, intake, and funding recommendations for analytics, ML, and GenAI initiatives
Define success metrics and track benefits for analytics and AI products and services
Lead, coach, and partner with multidisciplinary analytics, BI, data science/ML, and vendor teams
Build a high-performing organization focused on customer value, operational excellence, and continuous learning
Partner with business and functional leaders to identify, shape, and deliver analytics and AI use cases
Translate business needs into product backlogs and release plans
Advise on KPI design, experimentation, model performance, adoption, change management, and training
Communicate priorities, timelines, risks, and decisions; establish executive-ready status reporting
Define and enforce standards for data products, semantic models, KPI definitions, model documentation, and lifecycle management
Ensure compliance with security, privacy, data retention, and regulatory requirements
Establish responsible AI practices, including use-case review, human-in-the-loop controls, drift/bias monitoring, incident response, and audit-ready evidence
Modernize analytics and AI platforms, including cloud data stacks, self-service BI, feature/model stores, and GenAI tooling
Implement scalable delivery and operations such as CI/CD, automated testing, observability, cost management, and reuse
Apply manufacturing-domain knowledge to align data models and analytics with plant, product, and order-management processes
Design dimensional models, star schemas, snowflake models, fact/dimension tables, and enterprise data models
Lead end-to-end ETL/ELT pipeline development, including ingestion, transformation, reconciliation, and loading
Drive data governance, data quality, and Master Data Management, including trust rules, match/merge logic, lineage, DQ dashboards, reconciliation, and MDM rule sets
Maintain data lineage, metadata, documentation, data dictionaries, mapping documents, and metadata-driven warehouse frameworks
Lead data warehouse projects and cross-functional collaboration across multiple business units
Modernize legacy warehouses and manage cloud-native data platforms

Requirements

What you’ll need

Bachelor’s degree in Information Technology, Data Analytics, Business, or a related field
8+ years of experience across enterprise analytics, business intelligence, and/or data science/ML delivery in a medium-to-large enterprise environment
Proven experience leading teams and portfolios delivering analytics products and AI solutions, including vendor management, roadmap execution, and stakeholder governance
Hands-on experience with Snowflake as an enterprise platform, including Cortex Analyst / Snowflake Intelligence, warehouse cost/performance tuning, and role-based access governance
Experience designing and operating a medallion architecture (Bronze/Silver/Gold)
Experience consolidating data from heterogeneous ERP and legacy source systems such as JDE, EBS, and SAP-based systems
Strong people leadership, coaching, and stakeholder management skills
Ability to translate business strategy into analytics and reporting solutions
Ability to manage multiple priorities in a fast-paced, matrixed environment
Experience delivering AI/ML or GenAI solutions in production, including MLOps practices and cross-functional delivery
Exposure to responsible AI/model risk management, enterprise data governance, and Agile/DevOps methodologies
Practical AI literacy and ability to use AI-enabled tools to enhance productivity, decision-making, and quality of work
Strong understanding of the manufacturing domain, preferably windows manufacturing
Advanced dimensional modeling using Kimball, Inmon, or Data Vault
Experience with ETL/ELT tools such as SSIS, ODI, and Matillion
Strong SQL engineering skills, including complex SQL, PL/SQL, stored procedures, materialized views, CTEs, and performance tuning
Experience with data lineage, metadata management, documentation, data dictionaries, mapping documents, and metadata-driven data warehouse frameworks
Cloud data warehousing exposure, particularly Snowflake, including legacy warehouse modernization and cloud-native data platforms

Benefits

Comp & perks

Bonus
Medical, dental, and vision benefits starting day 1
PTO
Paid holidays
Flexible Spending Account (FSA)
Life insurance
Long-term disability (LTD)
Short-term disability (STD)
401(k)
Employee Assistance Program (EAP)
Discount programs
Tuition reimbursement
Training
Professional development