NOC 21223Canada · 2026STAR method

    Data Analyst Interview Questions (Canada)

    20+ Data Analyst interview questions for Canadian fintech, SaaS and banking (NOC 21223) — SQL, dashboards, and stakeholder scenarios.

    What to expect

    Data Analyst interviews in Canada (NOC 21223) usually combine a SQL test, a case study (build a metric / interpret a dashboard), and a stakeholder behavioural round. Be ready to defend trade-offs (CTE vs subquery, dbt vs ad-hoc, fact vs dimension).

    See the matching NOC 21223 guide, the resume example, and the cover letter example.

    Behavioural questions

    1. Tell me about yourself.
    2. Why do you want to work here?
    3. Tell me about a time you handled a difficult coworker.
    4. Describe a time you had to meet a tight deadline.
    5. Tell me about a mistake you made at work and what you learned.
    6. Walk me through a time you had to learn something new quickly.
    7. Describe a situation where you had to push back on a stakeholder.

    Data Analyst-specific questions

    1. Walk me through a SQL query you're proud of.
    2. How would you investigate a sudden 12% drop in conversion?
    3. When do you reach for a window function vs a self-join?
    4. How do you handle a stakeholder who disagrees with your numbers?
    5. Walk me through a dashboard you built — what would you change now?
    6. Difference between fact and dimension tables — and how dbt fits in.
    7. Tell me about a time your analysis changed a business decision.

    Culture-fit questions

    1. Where do you see yourself in 3 years?
    2. What's your salary expectation?
    3. Why are you leaving your current role?
    4. How do you handle feedback?
    5. What's your preferred working style — independent or team-based?
    6. Do you have questions for us?

    STAR-method sample answer

    Question: Tell me about a time your analysis prevented revenue loss.

    Situation. At Lightspeed I noticed a recurring chargeback pattern affecting one merchant cohort.

    Task. Quantify the loss and propose a rule before the next quarter close.

    Action. I ran a cohort analysis in BigQuery, isolated the signal to 3 merchant categories with a 4x baseline chargeback rate, and partnered with the risk team to ship a velocity rule.

    Result. $1.6M in chargebacks prevented over six months and the rule template was extended to 5 more merchant cohorts.

    Smart questions to ask back

    1. What does success look like in the first 90 days?
    2. Who would I be working with day-to-day, and how is the team structured?
    3. What's the biggest challenge facing this team right now?
    4. How is performance measured and reviewed?
    5. What do you enjoy most about working here?

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