IT Data Science Principal, Data Warehouse

This is a fully remote position, open to applicants in North Carolina.

📋 Description

• Create enterprise analytics and AI roadmaps that align with business strategy, value, and feasibility.

• Set prioritization, intake, and funding recommendations for analytics, machine learning, and generative AI initiatives.

• Establish success metrics and monitor benefits for analytics and AI products and services.

• Lead, mentor, and collaborate with multidisciplinary teams in analytics, business intelligence, data science/machine learning, and vendors.

• Build a high-performing organization aimed at delivering customer value, operational excellence, and ongoing learning.

• Collaborate with business and functional leaders to identify, shape, and implement analytics and AI use cases.

• Convert business needs into product backlogs and release strategies.

• Provide guidance on KPI design, experimentation, model performance, adoption, change management, and training.

• Communicate priorities, timelines, risks, and decisions; produce executive-ready status reports.

• Define and uphold standards for data products, semantic models, KPI definitions, model documentation, and lifecycle management.

• Ensure adherence to security, privacy, data retention, and regulatory requirements.

• Establish responsible AI practices, including use-case reviews, human-in-the-loop controls, drift/bias monitoring, incident response, and audit-ready documentation.

• Modernize analytics and AI platforms, including cloud data stacks, self-service BI, feature/model stores, and generative AI tools.

• Implement scalable delivery and operations such as CI/CD, automated testing, observability, cost management, and reuse.

• Utilize manufacturing-domain knowledge to align data models and analytics with plant, product, and order-management processes.

• Design dimensional models, including star schemas, snowflake models, fact/dimension tables, and enterprise data models.

• Oversee end-to-end ETL/ELT pipeline development, encompassing ingestion, transformation, reconciliation, and loading.

• Drive data governance, data quality, and Master Data Management, including trust rules, match/merge logic, lineage, data quality dashboards, reconciliation, and MDM rule sets.

• Maintain data lineage, metadata, documentation, data dictionaries, mapping documents, and metadata-driven warehouse frameworks.

• Lead data warehouse initiatives and facilitate cross-functional collaboration across various business units.

• Modernize legacy data warehouses and manage cloud-native data platforms.

⛳️ Requirements

• Bachelor's degree in Information Technology, Data Analytics, Business, or a related field.

• Over 8 years of experience in enterprise analytics, business intelligence, and/or data science/machine learning delivery within a medium to large enterprise setting.

• Demonstrated experience in leading teams and portfolios that deliver analytics products and AI solutions, including vendor management, roadmap execution, and stakeholder governance.

• Hands-on experience with Snowflake as an enterprise platform, covering Cortex Analyst/Snowflake Intelligence, warehouse cost/performance tuning, and role-based access governance.

• Familiarity with designing and operating a medallion architecture (Bronze/Silver/Gold).

• Experience consolidating data from diverse ERP and legacy source systems such as JDE, EBS, and SAP-based systems.

• Strong leadership, coaching, and stakeholder management skills.

• Ability to translate business strategy into analytical and reporting solutions.

• Capability to manage multiple priorities in a fast-paced, matrixed environment.

• Experience delivering AI/ML or generative AI 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 the ability to utilize AI-enabled tools to boost productivity, decision-making, and work quality.

• Strong understanding of the manufacturing domain, preferably in windows manufacturing.

• Proficiency in advanced dimensional modeling using Kimball, Inmon, or Data Vault methodologies.

• Experience with ETL/ELT tools such as SSIS, ODI, and Matillion.

• Strong SQL engineering capabilities, including complex SQL, PL/SQL, stored procedures, materialized views, common table expressions, and performance tuning.

• Familiarity with data lineage, metadata management, documentation, data dictionaries, mapping documents, and metadata-driven data warehouse frameworks.

• Exposure to cloud data warehousing, particularly with Snowflake, including legacy warehouse modernization and cloud-native data platforms.

🏝️ Benefits

• Bonus

• Medical, dental, and vision benefits starting on day 1

• Paid time off (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