IT Data Science Principal, Data Warehouse

Cornerstone Building Brands

. Develop the enterprise analytics and AI roadmap, aligning use cases and investments with business strategy, value, and feasibility .

Posted 11/12/2026full-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, aligning business strategy with analytics initiatives, and leading cross-functional teams in delivering AI solutions. Proficient in managing data governance, implementing responsible AI practices, and modernizing analytics platforms using cloud technologies.

Highest-signal resume keywords

Snowflake SnowPro CertificationEnterprise Analytics DeliveryAI/ML Solution ImplementationData Governance and Quality ManagementCross-Functional Team Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPL/SQLETL/ELT Pipeline DevelopmentDimensional ModelingData Warehouse ManagementAnalytics Product DevelopmentMLOps PracticesMedallion ArchitectureData Lineage AnalysisKPI Design

Soft Skills

People LeadershipStakeholder ManagementCoachingChange ManagementCommunication

Tools & Technologies

SnowflakeSSISODIMatillionCortex AnalystGenAI ToolingSelf-Service BICloud Data StacksData Governance ToolsAnalytics Platforms

Certifications & Qualifications

Snowflake SnowPro Certification

Industry Keywords

Enterprise AnalyticsBusiness IntelligenceData ScienceResponsible AIAgile MethodologiesDevOpsManufacturing Domain KnowledgeERP SystemsData Quality DashboardsModel Risk Management

Tech Stack

Tools & technologies

CloudERPETLMatillionSnowflakeSQLSSISVault

About the role

Key responsibilities & impact

Develop the enterprise analytics and AI roadmap, aligning use cases and investments 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 engineering, BI, data science/ML, and vendor teams
Set delivery quality, documentation, testing, and responsible AI standards; build development plans and career pathways
Partner with business and functional leaders to identify 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 through executive-ready reporting
Define and enforce standards for data products, semantic models, KPI definitions, model documentation, and lifecycle management
Ensure compliance with security, privacy, 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 CI/CD, automated testing, observability, and cost management for scalable analytics and AI delivery
Apply manufacturing-domain knowledge to align data models and analytics with plant, product, and order-management processes
Apply dimensional modeling using Kimball, Inmon, and Data Vault methods
Lead ETL/ELT pipeline development for ingestion, transformation, reconciliation, and loading using SSIS, ODI, and Matillion
Drive data governance, data quality, MDM, lineage analysis, DQ dashboards, reconciliation, and MDM rule sets
Write and optimize complex SQL, PL/SQL, stored procedures, materialized views, and CTEs
Maintain data lineage, metadata, data dictionaries, mapping documents, and data warehouse frameworks
Lead data warehouse projects and cross-functional collaboration across multiple business units
Modernize legacy warehouses and manage Snowflake cloud-native data platforms using medallion architecture

Requirements

What you’ll need

Bachelor’s degree in Information Technology, Data Analytics, Business, or a related field
Snowflake SnowPro Certification Required
8 plus 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, including JDE, EBS, SAP-based systems, and similar
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 environments, including MLOps practices and cross-functional delivery
Exposure to responsible AI/model risk management, enterprise data governance, and Agile/DevOps delivery methodologies
Practical AI literacy and ability to use AI-enabled tools to enhance productivity, decision-making, and quality of work
Must be at least 18 years of age to apply

Benefits

Comp & perks

Bonus
Medical, dental, and vision benefits starting day 1
401k
PTO
Paid holidays
FSA
Life insurance
LTD
STD
EAP
Discount programs
Tuition reimbursement
Training
Professional development