Top Consulting Data Engineering Jobs in Chicago, IL

Lead the design and implementation of enterprise-scale Knowledge Graphs and Semantic AI solutions, integrating graph intelligence and Generative AI. Manage cross-functional teams in data architecture and governance.

The role involves leading data architecture strategies and driving innovation in data solutions while ensuring compliance with governance policies. Responsibilities include translating data requirements into technical plans, overseeing advanced data technologies, and fostering collaboration among stakeholders.

Lead client-facing data solutioning and pre-sales efforts for Consumer verticals, design executable data architectures, support pursuit to close, and provide ~50% hands-on delivery and architectural oversight while ensuring information security and data privacy compliance.

This position involves supporting client-based data analytics and engineering projects, utilizing SQL, Python, or R, and presenting findings clearly.

This role involves leading the Data & AI team, building modern data platforms using Microsoft technologies, overseeing project delivery, and mentoring team members while engaging with clients.

The AI Data Specialist builds and maintains data pipelines, models, and integrations for AI systems, working closely with clients to ensure data quality and effective communication. They manage end-to-end data delivery for multiple projects in a fast-paced environment, translating complex problems into clear solutions.

The Senior Data Engineer will work with data tuning on relational databases, utilize big data technologies, and coordinate with teams. A strong academic background and experience with large datasets are required.

The Data Engineer will develop and maintain AI context data capabilities, create data pipelines, ensure operational excellence, and follow compliance protocols. Responsibilities include data ingestion, retrieval quality improvements, and semantic layer implementation for AI integration within healthcare organizations.

Lead and implement data and analytics solutions, architect data systems, provide assessments and roadmaps, and mentor teams in a consulting environment.

Design and build scalable cloud-native data pipelines and models to produce trusted, analysis-ready data. Ensure data quality, governance, and privacy controls, apply software engineering best practices, enable BI and AI/ML consumption, and collaborate with clients and cross-functional teams.