Data and AI Architect

Kforce has a client in Riverwoods, IL that is seeking an experienced Data & AI Architect to define and drive the data architecture strategy that powers enterprise AI, analytics, and machine learning initiatives. This role is responsible for designing scalable, AI-ready data ecosystems that support advanced analytics, generative AI, agentic AI, and intelligent automation solutions. The ideal candidate combines deep technical expertise in modern data platforms with a strong understanding of AI data requirements, governance, lineage, and enterprise architecture principles. Responsibilities:

• Define and maintain enterprise data architecture supporting AI, machine learning, and analytics initiatives
• Design scalable data models, pipelines, and integration patterns across cloud and enterprise platforms
• Establish standards for data ingestion, transformation, storage, governance, and consumption
• Architect solutions that unify structured and unstructured data into AI-ready datasets
• Develop and maintain data catalog, lineage, metadata, and data governance frameworks
• Partner with Data Engineering, AI/ML Engineering, Analytics, and Platform teams to ensure high-quality, reliable data foundations for AI initiatives
• Evaluate and recommend modern data technologies, integration tools, vector databases, and AI-focused data platforms
• Support enterprise data lake and modern data platform initiatives
• Create reference architectures, standards, data flow designs, and implementation guidance
• Drive architecture decisions that balance business value, scalability, security, performance, and cost
• Present architecture recommendations and technical strategies to both technical and executive stakeholders
• Stay current on emerging cloud data, AI infrastructure, and enterprise data architecture trends

Requirements:

• Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, or a related field (or equivalent experience)
• 8+ years of experience in Data Architecture, Data Engineering, Enterprise Data Management, or related disciplines
• 3+ years of experience designing and delivering data solutions supporting AI and machine learning workloads
• Deep expertise with cloud data platforms such as Snowflake, Google BigQuery, or equivalent technologies
• Experience designing and supporting enterprise data lake, data warehouse, or data mesh architectures
• Strong understanding of data modeling, ETL/ELT frameworks, data integration, and modern data architecture patterns
• Experience implementing data governance, metadata management, data cataloging, and lineage solutions
• Knowledge of AI/ML data requirements including feature engineering, vector embeddings, retrieval-augmented generation (RAG), and unstructured data processing
• Strong SQL skills and working knowledge of Python or similar scripting languages
• Excellent communication skills with the ability to translate technical concepts for business stakeholders

Preferred Qualifications:

• Relevant certifications such as SnowPro, GCP Professional Data Engineer, AWS Data Analytics, or equivalent
• Experience with advanced Snowflake capabilities, including Snowpark, Cortex, Data Sharing, and Dynamic Tables
• Experience with Google Cloud Platform services such as Vertex AI, Dataflow, Pub/Sub, and Cloud Storage
• Experience with vector databases, semantic search, knowledge graphs, ontologies, or AI-enabled knowledge architectures
• Familiarity with Model Context Protocol (MCP) or similar AI-to-data integration frameworks
• Experience supporting large-scale enterprise AI, analytics, or digital transformation initiatives