Student, Quality Engineering Analyst (Winter 2027)

Sunlife; Southwestern Ontario; Hybrid; CAD 45,000 - 60,000; Full time

Job summary

Sun Life is inviting students to join the Quality Engineering Analytics team to learn data engineering, analytics and AI within a collaborative, hybrid setting. You will work on QEA 360 data pipelines, dashboards and data-quality controls while exploring agentic AI capabilities that support engineering outcomes.

The role emphasizes hands‑on learning, problem solving and clear communication as you contribute to real data projects and practical AI experiments under guidance from experienced

Qualifications

• Enrolled in a post‑secondary program with graduation date in 2027 or later.
• Interest in data, software engineering, QA, automation or AI‑enabled product development.
• Foundational Python/Java/JS and SQL knowledge.
• Ability to analyze problems, test assumptions and explain findings clearly.
• Curiosity about agentic AI and safe, responsible use.

Responsibilities

• Assist with QEA 360 data pipelines, dashboards and data quality checks.
• Support data ingestion, validation and analytics across sources like qTest and Jira.
• Contribute to AI use cases, proofs of concept and experiments.
• Help define test scenarios and review agent outputs for accuracy.
• Build analytics and visualizations to tell data stories for leaders.

Skills

Python

SQL

Communication

Problem-solving

Curiosity about AI

Education

Pursuing CS/SE/DS (graduation Apr 2027+)

Tools

AWS S3

AWS Glue

AWS Redshift

AWS Lambda

SageMaker

Amazon Bedrock

Job description

At Sun Life,we’redriven by our Purpose: helping our Clientsachieve lifetime financial security and live healthier lives. Our values shape how we work: caring, authentic, bold, inspiring, and impactful.

Our 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.

Job Description

Join 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.

What will you do?

• Support 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.
• Improve 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.
• Contribute 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.
• Evaluate 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.
• Build 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.
• Research emerging practices: Explore developments in agentic AI, AI assurance, analytics and Quality Engineering, then summarize practical implications and recommendations for the team.
• Work across teams: Collaborate with Quality Engineering, Enterprise DevOps, AI enablement teams and platform partners to deliver small yet useful increments of work.
• Document and share what you learn: Create clear technical notes, user guidance and demonstrations so that experiments and improvements can be reused and supported.

What do you need to succeed?

• Currently 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
• Demonstrated interest in data, software engineering, Quality Engineering, automation or AI‑enabled product development.
• Foundational programming or scripting skills in Python, Java, JavaScript, or a similar language.
• Foundational knowledge of SQL, data structures, APIs, or database concepts.
• Ability to analyze a problem, test assumptions, and explain findings clearly.
• Curiosity about agentic AI, including how agents reason over context, use tools, execute workflows and produce evidence that people can evaluate.
• Comfort learning unfamiliar tools and technologies with support from experienced team members.
• Clear written and verbal communication skills and the ability to work collaboratively in a team environment.
• Attention to detail and a responsible approach to data, privacy, security and AI use.

Preferred Skills And Experience

• Hands‑on experience from coursework, personal projects, hackathons or prior work using Python and SQL.
• Exposure to cloud services, especially AWS data or AI services such as S3, Glue, Redshift, Lambda, SageMaker or Amazon Bedrock.
• Exposure to AI agents, large language models, prompt design, retrieval‑augmented generation, tool use or workflow orchestration.
• Experience with data visualization or business intelligence tools such as QuickSight, Power BI or Grafana.
• Familiarity with automated testing, CI/CD, Git, APIs or Agile product delivery.
• An understanding of responsible AI concepts such as evaluation, guardrails, explainability, traceability, and human oversight.
• Experience turning technical analysis into a concise presentation, demo or recommendation.

What is in it for you?

• Practical experience with enterprise Quality Engineering data, analytics and AI‑enabled workflows.
• Exposure to current agentic AI work, with an emphasis on evaluation, trust and responsible use rather than AI experimentation alone.
• Opportunities to contribute real code, analysis, testing, dashboards and documentation with coaching from experienced engineers and analysts.
• A collaborative environment where students are encouraged to ask questions, test ideas, and demonstrate what they have learned.
• Experience working across engineering, data, analytics, platforms and client teams.
• A flexible and inclusive workplace focused on continuous learning and meaningful outcomes.

Why join QEP?

The 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.

The 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.

Eligible 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

Diversity 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.

Persons with disabilities who need accommodation in the application process, or those needing job postings in an alternative format, may e-mail a request to [e-mail].

We 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.

We may use artificial intelligence to support candidate sourcing, screening, interview scheduling.

We thank all applicants for showing an interest in this position. Only those selected for an interview will be contacted.

Job Category

Temporary Employee

Posting End Date

04/11/2026