QA Engineer, Senior ( Automation , Ontology & Canonical Data Modeling )

The Quality Senior Analyst — Ontology & Canonical Data Modeling owns validation and quality assurance for Infor's Data Fabric ontology and canonical data model artifacts, including SHACL/SPARQL-based test assertions and cross-ERP mapping validation. The role requires 5+ years of QA/data-quality testing experience; no prior ontology/SPARQL experience is required, as this is built through a structured internal ramp program. A Typical Day in the Life Includes: Technology Environment Semantic web / ontology testing (learned on the job): SPARQL-based test assertions, SHACL constraint validation, Apache Jena, Fuseki Canonical data modeling: Cross-ERP mapping validation, master data concepts, data lineage Testing & automation: Test design, defect management, regression suites, CI/CD-integrated test automation Application context: SQL, basic scripting; working familiarity with Java/Spring-based services under test Cloud platform: AWS (or equivalent) — basic working knowledge Data Fabric platform: Infor Data Fabric integration pipelines and canonical schema examples Primary Responsibilities • Progress through the Basic → Advanced learning map with a quality/testing focus, passing checkpoints on schedule. • Author and maintain SHACL/SPARQL-based validation rules and regression test suites. • Validate canonical mappings for completeness and correctness across ERP source systems. • Track, report, and drive resolution of data-quality defects and mapping gaps. • Partner with engineers on acceptance criteria and quality standards for new deliverables. Basic Qualifications: Must-Have Skills — Mandatory Screening Criteria • 5+ years of QA/testing experience. • Experience testing data quality, ETL, or data integration/migration projects. • Strong SQL skills and basic test-automation scripting ability. • Strong analytical and defect-documentation skills. • Demonstrated learning agility to pick up SPARQL/SHACL-based testing techniques. Good-to-Have Skills — Candidate Differentiators • Experience testing master data management or cross-system integration projects. • Familiarity with test automation frameworks and CI/CD pipelines. • Any prior exposure to graph databases, RDF, or rule-based validation. • Experience with ERP data models. Preferred Qualifications: Preferred Experience • Master data management or cross-system integration testing. • Test automation and CI/CD-integrated quality gates. • Exposure to graph/semantic data or rule-based validation systems. • ERP-domain testing experience. Key Performance Indicators • On-time progression through the learning-map checkpoints relevant to quality/testing. • Defect detection rate and quality of defect reports for canonical/ontology artifacts. • Coverage and reliability of SHACL/SPARQL-based regression test suites. • Reduction in production data-quality escapes over time. Success Profile • Builds reliable, maintainable validation suites for evolving ontology and canonical artifacts. • Becomes the team's go-to expert for semantic-data quality and regression risk. • Partners effectively with engineers to shift quality left in the delivery process. • Clearly documents and communicates data-quality risks to the Team Leader and stakeholders.