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📁
Lead Software Engineer
📅
CREQ254972 Requisition #

Quality Assurance Lead
Workstream: Operational Excellence & Offshore Delivery

Role Purpose
Owner of the testing and validation of data products, ensuring that the data is accurate, reliable, and fit for purpose before being released to the business.

Accountabilities
* Coordinate nearshore resources to align validation activities.
* Own the definition, tracking, and reporting of Data Quality KPIs.
* Own the test strategy and technical issue tracking/resolution.
* Ensure the testing team uses standardized test plans, scripts, and execution methods.
* Identify opportunities to drive efficiencies through testing automation and tooling.

Responsibilities
* Define and own the data test strategy (Unit, Integration, Regression, UAT support).
* Define data quality standards and acceptance criteria for data products.
* Lead and coordinate QA resources to deliver against project timelines.
* Design and implement automated data validation frameworks.
* Ensure testing results are visible, traceable, and provide actionable insights.
* Improve the development lifecycle by reducing rework and identifying data issues earlier.

Quality Assurance Lead
Workstream: Operational Excellence & Offshore Delivery

Role Purpose
Owner of the testing and validation of data products, ensuring that the data is accurate, reliable, and fit for purpose before being released to the business.

Accountabilities
* Coordinate nearshore resources to align validation activities.
* Own the definition, tracking, and reporting of Data Quality KPIs.
* Own the test strategy and technical issue tracking/resolution.
* Ensure the testing team uses standardized test plans, scripts, and execution methods.
* Identify opportunities to drive efficiencies through testing automation and tooling.

Responsibilities
* Define and own the data test strategy (Unit, Integration, Regression, UAT support).
* Define data quality standards and acceptance criteria for data products.
* Lead and coordinate QA resources to deliver against project timelines.
* Design and implement automated data validation frameworks.
* Ensure testing results are visible, traceable, and provide actionable insights.
* Improve the development lifecycle by reducing rework and identifying data issues earlier.

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