Qa Engineer

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.