Enterprise Data Architect, Data, Analytics & AI
Job Description:
• Partner with the VP of Data & Analytics to shape enterprise data strategy with business and technology leaders, including problem framing, value hypotheses, and measurable outcomes
• Lead architecture for enterprise data solutions, including data modeling, enterprise analytics, integrations, and data DevOps
• Develop and maintain data models that reflect business processes and enable reporting, self-service analytics, and AI use cases
• Establish and promote best practices for data governance, data quality, and data security across the organization
• Align data architecture to business goals and Technology strategy by partnering with stakeholders to understand business processes, pain points, and the decisions the data must support
• Design and implement a medallion architecture in Snowflake (Bronze, Silver, Gold, and semantic layers) to support enterprise analytics and AI
• Define and maintain business questions, KPIs, and semantic definitions so the semantic layer is trusted, consistent, and usable for analytics and AI applications
• Partner with business and technical stakeholders across key systems (OMS, ERP, CRM, transactional databases) to understand use cases and design data products that support them
• Ensure data is cleansed, transformed, and documented for reliable analytical and AI consumption
• Create and maintain architecture diagrams, data dictionaries, data flow documentation, and implementation plans
• Research and stay current on AI/LLM and agentic system capabilities, architectures, and tooling; identify opportunities to apply them to data engineering, analytics, and operational workflows
• Participate in occasional after-hours support as needed (nights/weekends).
Requirements:
• Proven experience as an enterprise data architect (or equivalent) with a strong focus on Snowflake
• Strong proficiency in SQL
• Deep understanding of data warehousing concepts, dimensional and relational modeling, and ELT/ETL pipelines
• Experience working with OMS, ERP, CRM, and other transactional systems
• Strong business acumen and the ability to lead discovery with stakeholders, frame problems, identify root causes, and define measurable outcomes for data and analytics solutions
• Applied knowledge of modern AI (LLMs) and agentic systems, including how to integrate them with data platforms and analytics use cases
• Demonstrated ability to evaluate AI/vendor options, design experiments, execute POCs, and communicate recommendations (tradeoffs, risks, cost, and expected value)
• Excellent communication skills with the ability to influence and align technical and business stakeholders
• Ability to create clear architecture diagrams, documentation, and delivery plans
• Familiarity with data governance, metadata management, and data quality frameworks
• Experience with master data management (MDM) tools and approaches.
Benefits:
• Nationwide coverage for Medical, Dental, Vision, Life, and Disability insurance
• Additional Voluntary Benefits
• 401(k) Retirement Savings Plan
• Health Savings Accounts (HSA)
• Flexible Spending Accounts (FSA)
• Partner with the VP of Data & Analytics to shape enterprise data strategy with business and technology leaders, including problem framing, value hypotheses, and measurable outcomes
• Lead architecture for enterprise data solutions, including data modeling, enterprise analytics, integrations, and data DevOps
• Develop and maintain data models that reflect business processes and enable reporting, self-service analytics, and AI use cases
• Establish and promote best practices for data governance, data quality, and data security across the organization
• Align data architecture to business goals and Technology strategy by partnering with stakeholders to understand business processes, pain points, and the decisions the data must support
• Design and implement a medallion architecture in Snowflake (Bronze, Silver, Gold, and semantic layers) to support enterprise analytics and AI
• Define and maintain business questions, KPIs, and semantic definitions so the semantic layer is trusted, consistent, and usable for analytics and AI applications
• Partner with business and technical stakeholders across key systems (OMS, ERP, CRM, transactional databases) to understand use cases and design data products that support them
• Ensure data is cleansed, transformed, and documented for reliable analytical and AI consumption
• Create and maintain architecture diagrams, data dictionaries, data flow documentation, and implementation plans
• Research and stay current on AI/LLM and agentic system capabilities, architectures, and tooling; identify opportunities to apply them to data engineering, analytics, and operational workflows
• Participate in occasional after-hours support as needed (nights/weekends).
Requirements:
• Proven experience as an enterprise data architect (or equivalent) with a strong focus on Snowflake
• Strong proficiency in SQL
• Deep understanding of data warehousing concepts, dimensional and relational modeling, and ELT/ETL pipelines
• Experience working with OMS, ERP, CRM, and other transactional systems
• Strong business acumen and the ability to lead discovery with stakeholders, frame problems, identify root causes, and define measurable outcomes for data and analytics solutions
• Applied knowledge of modern AI (LLMs) and agentic systems, including how to integrate them with data platforms and analytics use cases
• Demonstrated ability to evaluate AI/vendor options, design experiments, execute POCs, and communicate recommendations (tradeoffs, risks, cost, and expected value)
• Excellent communication skills with the ability to influence and align technical and business stakeholders
• Ability to create clear architecture diagrams, documentation, and delivery plans
• Familiarity with data governance, metadata management, and data quality frameworks
• Experience with master data management (MDM) tools and approaches.
Benefits:
• Nationwide coverage for Medical, Dental, Vision, Life, and Disability insurance
• Additional Voluntary Benefits
• 401(k) Retirement Savings Plan
• Health Savings Accounts (HSA)
• Flexible Spending Accounts (FSA)