{"id":3353985,"url":"https://alion.io/job/sun-life-student-quality-engineering-analyst-winter-2027","title":"Student, Quality Engineering Analyst (Winter 2027)","company":{"id":2375471,"name":"Sun Life","domain":"sunlife.com.vn","url":"https://alion.io/company/sunlife-com-vn","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"Analytics","role_family":"Analytics","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Waterloo, Canada","Toronto, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":44000,"max_usd":88000,"period":"year","method":"role_country_seniority_unknown","sample_n":470},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"JavaScript","optional":false},{"name":"Jira","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Agile","optional":true},{"name":"Amazon Redshift","optional":true},{"name":"Amazon S3","optional":true},{"name":"Amazon SageMaker","optional":true},{"name":"AWS","optional":true},{"name":"AWS Bedrock","optional":true},{"name":"AWS Lambda","optional":true},{"name":"CI/CD","optional":true},{"name":"Function Calling","optional":true},{"name":"Git","optional":true},{"name":"Grafana","optional":true},{"name":"LLM Guardrails","optional":true},{"name":"Platform Engineering","optional":true},{"name":"Power BI","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-10-27T19:26:10Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-30T05:50:18Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"At Sun Life, we’re driven by our Purpose: helping our Clients achieve lifetime financial security and live healthier lives. Our values shape how we work: caring, authentic, bold, inspiring, and impactful.\nOur student and new graduate programs offer a chance to explore Sun Life from the inside. You’ll make a difference in the lives of our customers and communities, while building the skills and experience that allow you to grow in a meaningful and rewarding way.\nJob Description:\nJoin the Quality Engineering Analytics (QEA) team and help turn Quality Engineering data into useful insight, automation and trusted AI-enabled capabilities. You will work with engineers and stakeholders on QEA 360 data pipelines, dashboards, data-quality controls and agentic AI use cases that help teams understand quality, risk, adoption and delivery outcomes. This is a hands-on learning role for a student who is curious about data, analytics, Quality Engineering and how Agentic AI can safely support real engineering workflows.\nWhat will you do?\nSupport QEA 360 data and analytics: Help ingest, validate and analyze Quality Engineering data from sources such as qTest, Jira, delivery pipelines and operational systems. Contribute to reliable data pipelines and well-defined metrics. \nImprove data quality and automated testing: Assist with data-integrity checks, pipeline testing, dashboard validation, and automation that improves the accuracy, reliability and supportability of QEA products. \nContribute to agentic AI use cases: Support proofs of concept and product experiments where AI agents analyze quality data, assist with defect and risk insights, or help automate multi-step Quality Engineering workflows. \nEvaluate AI-generated outcomes: Help define test scenarios, expected evidence and quality checks for agent outputs. Review results for accuracy, usefulness, traceability, and appropriate human oversight. \nBuild analytics and visualizations: Use dashboards, reporting tools and clear data storytelling to help clients and leaders understand trends, platform usage, AI adoption and opportunities for improvement. \nResearch emerging practices: Explore developments in agentic AI, AI assurance, analytics and Quality Engineering, then summarize practical implications and recommendations for the team. \nWork across teams: Collaborate with Quality Engineering, Enterprise DevOps, AI enablement teams and platform partners to deliver small yet useful increments of work. \nDocument and share what you learn: Create clear technical notes, user guidance and demonstrations so that experiments and improvements can be reused and supported. \nWhat do you need to succeed?\nCurrently enrolled in a post-secondary program in Computer Science, Software Engineering, Data Science, Data Analytics, Information Systems, Business Technology Management, or a related field with a graduation date of April 2027 or later\nDemonstrated interest in data, software engineering, Quality Engineering, automation or AI-enabled product development. \nFoundational programming or scripting skills in Python, Java, JavaScript, or a similar language. \nFoundational knowledge of SQL, data structures, APIs, or database concepts. \nAbility to analyze a problem, test assumptions, and explain findings clearly. \nCuriosity about agentic AI, including how agents reason over context, use tools, execute workflows and produce evidence that people can evaluate. \nComfort learning unfamiliar tools and technologies with support from experienced team members. \nClear written and verbal communication skills and the ability to work collaboratively in a team environment. \nAttention to detail and a responsible approach to data, privacy, security and AI use. \nPreferred skills and experience\nHands-on experience from coursework, personal projects, hackathons or prior work using Python and SQL. \nExposure cloud services, especially AWS data or AI services such as S3, Glue, Redshift, Lambda, SageMaker or Amazon Bedrock. \nExposure to AI agents, large language models, prompt design, retrieval-augmented generation, tool use or workflow orchestration. \nExperience with data visualization or business intelligence tools such as QuickSight, Power BI or Grafana. \nFamiliarity with automated testing, CI/CD, Git, APIs or Agile product delivery. \nAn understanding of responsible AI concepts such as evaluation, guardrails, explainability, traceability, and human oversight. \nExperience turning technical analysis into a concise presentation, demo or recommendation. \nWhat is in it for you?\nPractical experience with enterprise Quality Engineering data, analytics and AI-enabled workflows. \nExposure to current agentic AI work, with an emphasis on evaluation, trust and responsible use rather than AI experimentation alone. \nOpportunities to contribute real code, analysis, testing, dashboards and documentation with coaching from experienced engineers and analysts. \nA collaborative environment where students are encouraged to ask questions, test ideas, and demonstrate what they have learned. \nExperience working across engineering, data, analytics, platforms and client teams. \nA flexible and inclusive workplace focused on continuous learning and meaningful outcomes. \nWhy join QEP?\nThe Enterprise Quality Engineering Platform helps teams build and deliver software with greater confidence. Our work spans data and analytics, automation, platform engineering, and AI-enabled Quality Engineering. As agentic systems become part of how software is built and tested, QEP is focused on both using AI to improve Quality Engineering and ensuring that AI-generated outcomes can be evaluated and trusted. You will join a team working on practical problems where data quality, engineering judgment and responsible AI all matter.\nThe Base Pay range is for the primary location for which the job is posted for. The Base Pay which you will be considered for will vary depending on the Campus program you are selected for.\nEligible Sun Life employees for various Campus Graduate programs will also participate in various incentive plans, payment under which is discretionary and subject to individual and company performance\nDiversity and inclusion have always been at the core of our values at Sun Life. A diverse workforce with wide perspectives and creative ideas benefits our Clients, the communities where we operate and all of us as colleagues. We welcome applications from qualified individuals from all backgrounds.\nPersons with disabilities who need accommodation in the application process, or those needing job postings in an alternative format, may e-mail a request to .\nWe are proud to be a hybrid organization that offers our employees the choice and flexibility to work from both the office and virtually based on the needs of the business, our Clients and you.\nWe may use artificial intelligence to support candidate sourcing, screening, interview scheduling.\nWe thank all applicants for showing an interest in this position. 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