logo

View all jobs

Quality Assurance Lead

Calgary or Edmonton, Alberta
Description of Work:

Our client has embarked on a major program to create an enterprise wide repository of modeled, certified data to support high value analytics, AI and data integration with client's applications and with partners outside. The program is seeking a Quality Assurance Lead to help establish the right quality processes, controls, and metrics for migrating and modeling data and for developing analytics on top of that data.

Responsibilities for the Role:
  • Data Delivery Quality controls: Identify, design, implement and monitor quality controls in the end to end processes of client’s data sourcing delivery, ingestion, modeling and view creation
  • User Acceptance Testing approach: Design and oversee the approach and execution for UAT
  • Reporting: Design and implement quality metrics and scorecard
  • Incident Tracking and Management: Oversee incident management
  • Problem Management: Design and implement problem management processes
  • Continuous Improvement: Identify continuous improvements to quality management processes. Plan, implement and document processes to ensure end quality objectives are met
  • Test Automation: Develop a test automation strategy, gain internal approvals and implement across the program
  • Supervise QA resources: Lead a small team of QA specialists and help drive quality processes throughout the development team
Required Skills and Experience:
  • Bachelor’s degree
  • Professional certification, such as Six Sigma, Quality Engineer, or Quality Auditor
  • Expert in quality assurance terminology, methods, and tools
  • Demonstrated experience as lead QA resource for large data intensive program
  • Demonstrated knowledge of testing best practices, version control practices and defect management practice
  • Demonstrated experience developing QA strategies on large, complex engagements
  • Ability to establish a positive and collaborative working relationship with other program team members
  • Demonstrated knowledge of a data lifecycle and the associated QA steps
Additional "nice to have" Experience:
  • Understanding of Agile/Scrum methodology and how QA functions within it
Powered by