Federal Government Clearance Level Required: NoneVacancy Type:About UsMaplesoft Group is currently seeking a Hybrid Data Knowledge Engineer for our client.Position SummaryThe Data Knowledge Engineer plays a critical role in enabling the organization’s transition toward AI-driven analytics and data navigation. This role is responsible for designing, developing, and maintaining the enterprise data knowledge graph—a structured network of metadata, business definitions, relationships, and governance policies that enables AI systems and analytics platforms to accurately interpret and navigate enterprise data.Working within the Data Governance team, the Data Knowledge Engineer ensures that enterprise data assets are described, connected, and governed in a way that supports trusted analytics, AI-driven insights, and responsible data usage across the organization.This role bridges data governance, data architecture, and analytics engineering to ensure that business meaning, data ownership, policies, and lineage are represented in a machine-readable format that supports modern data platforms and AI interfaces.Key ResponsibilitiesDesign and maintain the enterprise data knowledge graph by connecting metadata across the organization’s data ecosystem. Responsibilities include:Defining relationships between data assets, business concepts, policies, and ownershipModeling connections between data products, datasets, semantic models, metrics,



and domainsEnsuring metadata relationships support AI-driven data discovery and navigationMaintaining graph integrity as data platforms and architectures evolveMetadata Integration and Architecture:Integrate metadata across enterprise platforms to create a unified metadata ecosystem.Lakehouse governance platforms (e.G., Databricks Unity Catalog)Analytics and semantic layers (e.G., Microsoft Fabric semantic models)Data pipelines and lineage systemsIdentity and access management systemsEnsure metadata relationships are captured and represented consistently across the ecosystem.Collaborate with analytics, data engineering, and domain teams to ensure semantic models accurately represent business meaning.Aligning semantic models with business glossary definitionsSupporting standardization of enterprise metricsEnsuring consistent interpretation of key business concepts across analytics assetsConnecting semantic models to underlying data products and datasetsGovernance Policy Enablement:Translate governance policies into machine-readable metadata and policy structures that support automated enforcement.Access control policiesTrust signals and certification indicatorsThis work supports agile governance capabilities, such as AI-mediated data access and trust-based query evaluation.Data Product Context and Ownership:Support the governance framework for enterprise data products by ensuring that critical metadata elements are defined and maintained.Data quality indicatorsThese elements become core nodes within the enterprise knowledge graph.AI Readiness and Data Context:Ensure enterprise data assets are described in ways that allow AI systems and copilots to interpret them accurately.Business definitions are clear and standardizedAuthoritative datasets are identified and documentedData relationships are well understoodGovernance policies are visible to AI navigation systemsRequired QualificationsExperience with enterprise metadata management and data catalog platformsKnowledge of up-to-date data architectures (lakehouse, medallion, data products)Experience with semantic data modeling and metrics layersFamiliarity with data lineage, metadata frameworks, and governance conceptsAbility to model relationships between data assets, business meaning, ownership, and policiesStrong collaboration skills across technical and business teamsPreferred technologiesDatabricks Unity CatalogKnowledge graph or ontology modeling conceptsCompensationSalary Range: $85.00 – $115.00 per hourSubmission DeadlineFriay, March 20, 2026How to ApplySubmit your resume (and cover letter) to:Or- https://www.Maplesoftgroup.Com/Careers/Career-OpportunitiesRecruitment ProcessOur recruitment process is led by human recruiters who review all applications and make the final hiring decisions. We use AI-assisted tools to help screen and organize applications. These tools do not replace human judgment, and all hiring decisions are made by people.Please note that data collected by the Company may be stored or processed on servers located outside of Canada.EEO StatementMaplesoft is an equal opportunity employer and welcomes applications from all qualified candidates. Accommodations are available upon request throughout the recruitment process.#J-18808-Ljbffr

📌 Data Knowledge Engineer - $85 - $115 An Hour (Courtice)
🏢 Maplesoft Group
📍 Courtice