Senior Data Quality & QA/QC Lead Engineer

KenWave Solutions; Mississauga; On-site; CAD 90,000 - 130,000; Full time

Job summary

KenWave Solutions is seeking a Lead Analyst, Data Quality & QA/QC to oversee the Data Quality Control and Pre-Processing Centre. You will guide analysts, ensure QA/QC across data and models, and review analyses before client delivery.

The role involves developing Python-based analytical workflows, managing PostgreSQL data models, and driving continuous improvements in data processing reliability and efficiency.

Qualifications

• Degree in engineering, computer science, data science, applied physics, acoustics, or related technical discipline, or equivalent experience.
• Demonstrated experience in engineering analysis, scientific data processing, QA/QC, or similar environment affecting client deliverables.
• Experience leading or mentoring analysts or technical staff in an operational delivery setting.
• Strong Python skills with experience developing analytical workflows, not just general apps.

Responsibilities

• Lead daily operation of Data Quality Control and Pre-Processing Centre with prioritization and analyst support.
• Define and apply data-quality standards, acceptance criteria, and QA/QC procedures across data processing stages.
• Review and approve analysis outputs, documenting material assumptions and corrections.
• Mentor analysts and provide technical direction to ensure consistent methods and QA/QC.
• Perform and oversee acoustic analysis, assess measurement quality, and investigate datasets.

Skills

Python

Data QA/QC

Analytical thinking

Communication

Education

Engineering or related degree

Tools

PostgreSQL

Python workflows

Job description

KenWave Solutions is seeking a Lead Analyst, Data Quality & QA/QC to oversee the Data Quality Control and Pre-Processing Centre. You will guide analysts, ensure QA/QC across data and models, and review analyses before client delivery.

The role involves developing Python-based analytical workflows, managing PostgreSQL data models, and driving continuous improvements in data processing reliability and efficiency.