Quality Assurance Lead
Engie is hiring a Quality Assurance Lead in Melbourne, Australia. Level rates it ; you can apply on Engie.
Level's read on this job
- Level rates this role Little AI ●○○○: aI is not part of the work.
- Level classifies it as a lead role.
- Level lists 653 other open roles at Engie.
- The role was posted in the last few days.
AI in this role
About the Role
We’re looking for a Quality Assurance Lead to shape and strengthen quality assurance across ENGIE Retail’s customer operations. You’ll use data, technology and quality insights to improve customer outcomes, strengthen compliance and identify opportunities for smarter, more effective ways of working.
- Own and continuously improve the quality assurance framework, including standards, scorecards, sampling, calibration and reporting.
- Lead quality monitoring across customer operations and delivery partners, ensuring consistent assessment of customer outcomes, compliance and process quality.
- Lead the implementation and governance of AI-enabled quality assurance, analytics and compliance monitoring solutions.
- Identify emerging customer, operational and regulatory risks, investigate root causes and support corrective actions that prevent recurrence.
- Turn quality, customer and operational data into practical insights that support better decisions, stronger controls and continuous improvement.
- Identify and assess automation and process improvement opportunities, measuring their impact on customer experience, efficiency, risk and cost.
About You
You’re an experienced quality or operational improvement professional who’s comfortable working in a complex, regulated customer environment. You’ll bring a strong understanding of quality assurance practices together with the ability to use data, technology and structured problem-solving to drive meaningful improvement.
- Relevant professional experience in quality assurance, operational excellence, process improvement, business analysis, automation or customer operations.
- Demonstrated experience developing, implementing or improving quality assurance frameworks in complex operational environments.
- Strong knowledge of quality monitoring, sampling methodologies, calibration, critical failure management and quality reporting.
- Experience using operational data, quality results, customer feedback and complaints to identify trends, root causes and improvement opportunities.
- Strong understanding of risk management, operational controls, compliance monitoring and issue escalation, ideally gained within a regulated customer environment.
- Experience with automation, AI or digital enablement, including customer operations technologies such as CRM, workflow, speech analytics or automated quality management tools.
At ENGIE, every talent has a role to play in accelerating the energy transition. Make a difference and enjoy a fulfilling professional experience. Take on exciting challenges and build a career path that reflects who you are. Join us and be part of the adventure of the century!
ENGIE is an equal opportunity employer, promoting diversity and committed to creating an inclusive environment for all. All applications are screened based on business needs, job requirements and individual qualifications, without any regard to origin, age, carer’s responsibilities, sexual orientation, gender identity, pregnancy, religion, marital status, health, disability or political opinions. Aboriginal and Torres Strait Islander peoples, people with disability, people from diverse cultural and linguistic backgrounds and people of the LGBTIQA+ community are encouraged to apply. Our differences are our strengths.
How we rate this
Quality Assurance Lead at Engie rates 21 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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