Enterprise Architect - Data and AI

This range is provided by Insight Global. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

$/yr - $/yr

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Insight Global is looking for a Data and AI Enterprise Architect to join their clients team. This candidate will develop data architecture across the organization, providing expertise, and resolving conflicts in data architecture projects by analyzing business needs and managing the quality of deliverables created. You will drive alignment on data architecture principles, foster cross-functional collaboration, and ensure that data capabilities are scalable and aligned with enterprise AI goals.

The Day-to-Day includes:

• Design and evolve enterprise-level semantic data models, including logical and conceptual models, ontologies, and domain definitions
• Partner with product, data, and engineering teams to define domain-driven data contracts that support AI, analytics, and operational needs
• Collaborate with governance, AI/ML, and metadata teams to support computational governance and automated metadata enrichment
• Evaluate AI-generated code for accuracy, performance, and clarity
• Build data architecture and applications that ensure reporting, analytics, data science, and data management and improve accessibility, efficiency, governance, processing, and quality of data
• Lead the standardization of metadata practices across domains, ensuring discoverability, lineage, and governance
• Enable scalable and interoperable semantic layers across data platforms (e.g., Lakehouse, Knowledge Graphs, Data Warehouses)
• Provide strategic guidance on data modeling techniques (3NF, dimensional, Data Vault, RDF/OWL) and drive adoption of best practices
• Strong collaboration skills, working cross-functionally with data product owners, engineers, data scientists, and governance teams
• Provide feedback that directly shapes the next generation of AI models
• Knowledge of Machine Learning Operations (MLOps) workflows and tools for deploying, managing, and monitoring AI models in production
• Extensive experience building big data pipelines

• Experience with Assess and Wealth Management from a data modeling perspective at the conceptual, logical and physical level
• 10+ years of experience with Data technologies (databricks, Neo4j, Pinecone etc)
• Familiarity with platforms like Alpha Data Platforms and Financial Services Cloud
• Data Modeling for front, middle and back office from an investment perspective
• Thorough understanding of Medallion Architectures (with key focus on designing for Lakebase using Delta Lake)
• Deploying the embedding models for handling the structured and unstructured data into a knowledge graph (neo4j with cipher queries)
• Bachelor’s degree

• How do they make Data ready for AI? (Conversational AI, Generative AI and Agentic AI)
• What is their understanding of Data Warehouse Architecture Evaluations

Mid-Senior level

Full-time

Other

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