Position Overview The Lead Analyst, Data Quality & QA/QC is responsible for the day-to-day technical and operational leadership of the Data Quality Control and Pre-Processing Centre. The role combines hands-on engineering analysis with analyst leadership, QA/QC ownership, technical review, and development of the data and software workflows supporting water-pipeline condition assessment. This position is suited to a technical lead who can move between troubleshooting complex datasets, improving analytical processes, and guiding a team delivering consistent client-ready results.

Key Responsibilities

- Lead the daily operation of the Data Quality Control and Pre-Processing Centre, including work prioritization, workload coordination, analyst support, and alignment with project delivery requirements.

- Define, maintain, and apply data-quality standards, acceptance criteria, and QA/QC procedures across field data, preprocessing, engineering analysis, and final data products.

- Review and approve analysis outputs before client delivery, confirming that required QA/QC checks are complete and that material assumptions, exceptions, and corrections are documented.

- Lead, mentor, and provide technical direction to analysts, with emphasis on consistent analytical methods, preprocessing, signal interpretation, QA/QC, and troubleshooting practices.

- Perform and oversee acoustic analysis for client projects, including assessment of measurement quality, identification of anomalous or unreliable data, and investigation of difficult datasets.

- Determine whether data-quality issues originate from field acquisition, sensor or system configuration, processing, or analysis assumptions, and work with field and project teams to resolve them.





- Lead root-cause investigations into recurring measurement or processing issues and translate findings into practical corrective actions, updated procedures, or system improvements.

- Establish and monitor practical operational KPIs covering data quality, processing throughput, turnaround, backlog, rework, and recurring quality issues, and use the results to identify improvement priorities.

- Drive continuous improvement through workflow standardization, automation, validation controls, and reduction of repetitive manual analysis steps.

- Contribute directly to the Python-based analysis application by developing and maintaining analytical workflows, data-processing tools, validation routines, testing, logging, and error handling.

- Develop and maintain PostgreSQL data models and supporting pipelines for analysis inputs, intermediate results, outputs, metadata, and project information, with appropriate traceability and reproducibility.

- Support dependency tracking and controlled precomputation of analysis results when upstream parameters or inputs change.

- Maintain clear technical documentation for analytical methods, QA/QC procedures, recurring issues, software workflows, and project-specific analysis decisions.

Qualifications and Experience

- Degree in engineering, computer science, data science, applied physics, acoustics, or a related technical discipline, or equivalent relevant technical experience.

- Demonstrated experience in engineering analysis, scientific data processing, technical QA/QC,



or a comparable workplace where data quality directly affects project or client deliverables.

- Experience leading, mentoring, or providing technical direction to analysts, engineers, or other technical staff in an operational delivery environment.

- Strong Python skills with practical experience developing or maintaining analytical, data-processing, or scientific workflows rather than solely general-purpose application development.

- Practical experience with PostgreSQL or a comparable relational database, including data modelling, structured storage of analytical results, and traceability of processing inputs and outputs.

- Experience working with sensor, signal, time-series, or other engineering measurement data and investigating anomalous, incomplete, failed, or unreliable measurements.

- Working knowledge of software quality practices such as validation, automated testing, logging, error handling, version control, and reproducible processing.

- Ability to investigate technical problems across data acquisition, processing, software, and analysis rather than treating each area as an isolated function.

- Strong written and verbal communication skills with the ability to document technical findings and work effectively with field, project, engineering, and software teams.

Preferred Qualifications

- Experience in acoustics and/or vibration analysis.

- Experience working directly with WAV files or recordings from acoustic, vibration, or other vibroacoustic sensors.

- Experience applying signal-processing techniques to troubleshoot real-world measurement data.

- Experience with pipeline condition assessment, infrastructure diagnostics, or another sensor-based engineering inspection environment.

📌 Lead Data and QA QC Analyst (Mississauga)
🏢 KenWave Solutions
📍 Mississauga