Knowledge Engineer

Associated Bank • US WI Remote, IL

8d • $92,610 - $158,760

About The Position

The Knowledge Engineer helps build the foundation for trusted, connected, and understandable data across the organization. The role partners with business and technology teams to create shared data definitions and semantic models that support decision-making, governance, and AI capabilities. It offers an opportunity to influence enterprise data strategy while developing expertise in modern data and knowledge technologies.

The position develops enterprise semantic models, ontologies, taxonomies, and knowledge graph structures to establish consistent business meaning across data domains. It defines and maintains business concepts, metadata standards, and data relationships; maps technical data from multiple systems to shared business definitions; and works with architecture, engineering, governance, AI, and business partners to deliver scalable semantic solutions. The role also advances data discovery, analytics, AI-ready data capabilities, metadata, lineage, and governance practices.

The role requires a bachelor's degree in a related field or an equivalent combination of education and experience, along with at least three years of experience with semantic technologies, data modeling, knowledge representation, graph databases, and semantic web standards, and at least three years working with modern data platforms and cross-functional teams on enterprise data solutions. Preferred qualifications include relevant additional experience and Neo4j Certified Professional or SnowPro Advanced certification.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Data Science, Knowledge Engineering, or a related field, or an equivalent combination of education and experience.
• At least 3 years of experience with semantic technologies, data modeling, knowledge representation, graph databases, and semantic web standards.
• At least 3 years of experience working with modern data platforms and collaborating across data architecture, engineering, and governance teams to deliver enterprise data solutions.

Nice To Haves

• Bachelor's degree in Data Science or a related discipline.
• At least 1 year of experience implementing or managing enterprise knowledge graph platforms or semantic technologies.
• At least 1 year of experience supporting enterprise data governance, metadata management, lineage, and data quality initiatives.
• Neo4j Certified Professional certification.
• SnowPro Advanced certification.

Responsibilities

• Develop enterprise semantic models, ontologies, taxonomies, and knowledge graph structures that create consistent business meaning across data domains.
• Define and maintain enterprise business concepts, metadata standards, and data relationships to support governance and regulatory compliance.
• Map technical data from multiple systems to shared business definitions and reusable semantic standards.
• Partner with data architecture, engineering, governance, AI, and business teams to translate business needs into scalable semantic solutions.
• Apply semantic web standards, graph technologies, and knowledge modeling practices to enable advanced data discovery and analytics.
• Design semantic frameworks that improve context, search, and knowledge-driven insights and support AI-ready data capabilities.
• Advance metadata, lineage, and governance best practices to promote enterprise data consistency.
• Comply with applicable policies, laws, and regulations; report suspicious activity, customer complaints, procedure violations, and ethical concerns as required.

Benefits

• Retirement savings including 401(k) and pension plans.
• Paid time off to volunteer in the community.
• Diversity-focused Colleague Resource Groups.
• Competitive salaries and professional development and advancement opportunities.
• Well-being programs and incentives.
• Parental leave.
• Employee stock purchase plan.
• Military benefits.
• Personal banking, loan, investment, and insurance benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level