Lead Data and QA QC Analyst

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 ateamdelivering 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 andsupportingpipelines 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.
Qualification sand 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 environment 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 with leak detection.
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.
This is a non-management position
This is a…