Insights Architect, Data & AI

Job Description

Primary Function of Position

We are seeking an experienced Insights Architect, Data & AI to shape and deliver scalable data, analytics, and AI capabilities that improve business decisions across operations. The initial focus will include Service Supply Chain, with opportunity to apply the same product and architecture leadership across other business domains over time.

This role sits at the intersection of business processes, enterprise applications, data, analytics, and AI. The ideal candidate combines technical depth with business curiosity and product thinking. They will partner with stakeholders to understand how work gets done, identify the decisions and problems that matter most, and translate them into reusable data products and technical solutions.

The architect will work across a transforming landscape that includes SAP and o9 as foundational business platforms and Snowflake as a core enterprise data platform. They will help establish trusted enterprise data, common metrics and KPIs, semantic models, and governed data products that enable self-service insights, advanced analytics, data science, and AI-assisted decision support.

We are looking for someone who can move fluidly between business and technical conversations, bring structure to ambiguity, recognize patterns across use cases, and influence teams to build durable capabilities rather than isolated solutions.

Essential Job Duties

• Develop a deep understanding of business processes, decisions, workflows, pain points, and desired outcomes across planning, execution, inventory, repair, and related operational areas.
• Partner with business leaders and domain experts to frame complex or ambiguous problems, distinguish symptoms from root causes, and identify where data, analytics, automation, or AI can materially improve decisions.
• Translate business problems into clear product capabilities, data requirements, analytical requirements, technical specifications, and scalable solution architectures.
• Lead the design of reusable data products that combine trusted data, business definitions, standardized metrics and KPIs, analytical models, lineage, governance, and semantic context.
• Architect capabilities across SAP, o9, Snowflake, and related platforms while balancing near-term outcomes with scalable patterns and long-term maintainability.
• Partner with data engineering teams to design data models, ETL/ELT pipelines, integration patterns, data quality controls, and analytical structures that support business-facing products.
• Design and evolve semantic models in Snowflake that make enterprise information easier to understand, discover, and consistently consume across analytics and AI use cases.
• Evaluate knowledge graphs, ontologies, and related semantic approaches to connect business entities, relationships, metrics, and operational context for richer investigation and root-cause analysis.
• Help move the organization from disconnected datasets and dashboards toward governed, reusable data products and trusted self-service analytics.
• Partner with data science and AI teams to provide well-defined, governed data and business context for advanced analytics, machine learning, and GenAI-enabled solutions.
• Recognize patterns across individual requests and convert them into common data products, architecture patterns, semantic models, standards, or reusable capabilities.
• Lead cross-functional business and technical conversations, evaluate alternatives and tradeoffs, and create alignment across business, product, application, architecture, engineering, analytics, and AI teams.
• Influence without direct authority, challenge assumptions constructively, and guide complex initiatives from problem definition through design, implementation, adoption, and continuous improvement.
• Communicate complex technical concepts in clear business language and translate business context into sufficient technical detail for delivery teams.
• Provide architectural guidance and coaching to engineers, analysts, architects, and product teams, raising the quality and consistency of solutions across the organization.

Qualifications

Qualifications

Required Skills and Experience

• Minimum 8 years of relevant experience in data and analytics architecture, data products, data warehousing, business intelligence, enterprise applications, or related disciplines.
• Demonstrated ability to learn complex business domains and translate business problems into scalable technical solutions and measurable outcomes.
• Proven experience designing and delivering data and analytics products from problem definition through implementation and adoption.
• Strong understanding of data architecture, data modeling, ETL/ELT, integration patterns, data quality, lineage, governance, and enterprise data warehousing.
• Hands-on proficiency with SQL and modern cloud data platforms such as Snowflake or comparable technologies.
• Experience developing metrics, KPIs, dimensional models, and semantic or business-facing data models.

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