QA Engineer, Senior

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.