캐나다 취업 | 데이터 분석가, 데이터 엔지니어 면접 질문 모음

회사 L

Financial Analytics 팀의 리더에게 직접 리포팅하는 신규 채용 포지션으로, 팀 내 두 번째 다이렉트 리포트가 될 예정입니다.

포지션 개요

• 팀 구성: Financial Data & Insights (8명)
• 속한 부서: Finance (총 500명 규모)
• 업무 성격: Engineering, Finance, Operations 부서와 cross-functional하게 협업하며, 데이터 분석, 문제 해결, 대시보드 개발(Tableau), 리포팅 작업 수행
• 사용 툴: SQL, Python, Tableau, Excel
• 중요 역량: SQL 실력, 분석적 사고, 협업 능력(team player)

인터뷰 프로세스 요약

1. 1차: 리크루터와의 30분 전화 인터뷰
2. 2차: Tech Lead와의 30분 화상 인터뷰
   • 보다 기술적인 질문 위주이나, 실시간 라이브 코딩 등은 없음
   • 기술 스택에 대한 경험과 실제 적용 사례 위주로 질문
3. 3차: 1시간 SQL 인터뷰
   • SQL 실력 검증
4. 최종 라운드: 팀원 2명과 각 30분 인터뷰

리크루터 인터뷰 질문 및 샘플 답변

1. Why are you specifically interested in our company?

Sample Answer:

I’m especially interested in your company because of your data-driven culture and the opportunity to work cross-functionally with engineering, finance, and operations. I’m excited by the challenge of working in a large finance organization and contributing to actionable insights through tools like Tableau and SQL.

2. Can you tell me about the team you currently work with?

Tip: cross-functional한 협업 경험을 중심으로 대답 준비

Sample Answer:

In my previous role, I worked closely with both engineering and business teams. For example, I partnered with the order fulfillment team and the IT department to automate manual processes using Power BI and Power Automate.

3. Are you comfortable working with SQL, Python, Tableau, and Excel?

Sample Answer:

Yes, I’m very comfortable with all four. I’ve built complex dashboards in Tableau, written Python scripts for data processing, and used advanced Excel functions and pivot tables. SQL is my daily tool for querying and analyzing data across systems.

Yes, I’m very comfortable with all of them.
At my internship, we had a manual reporting process that took over 2 hours each day (Situation/Task).
I created a Power BI dashboard and used SQL queries to automate the data source (Action).
This reduced daily reporting time to under 15 minutes (Result).

4. Would working in the office on Monday, Wednesday, and Thursday work for you?

Sample Answer:

Yes, that schedule works well for me.

5. If we were to offer you the position, when would you be available to start?

Sample Answer:

I can be available to start as early as #, but I’m also flexible depending on your timeline.

6. The salary range is CAD # to  #. Does that align with your expectations?

Sample Answer:

Yes, that range aligns with my expectations.

 

회사 V

15분 리크루터 인터뷰 정리

1. Can you briefly introduce yourself? (1–2 minutes)

Sample Answer:

Sure! I recently completed an Honours Specialization in # and worked as a Data Engineer Intern at #. During my internship, I built automated dashboards and streamlined order allocation processes using SQL, Power BI, and Power Automate. I enjoy turning raw data into actionable insights and working with cross-functional teams to solve real business problems. I’m really excited to bring that experience into a fast-paced and data-driven team like yours.

 

2. Could you give me an example of your work at a previous role? It could be a challenge you faced or a problem you discovered. How did you solve it?

Tip: STAR 기법 사용 – 문제 발견 → 해결 과정 → 결과

Sample Answer:

At #, I noticed our order allocation team spent over 2 hours a day manually updating spreadsheets.
I analyzed their workflow and identified that much of it could be automated.
So, I developed a Power BI dashboard with automated SQL queries to replace the manual steps.
As a result, the process was reduced to under 15 minutes per day and significantly lowered the risk of human error.

 

3. Do you think there are similarities between what you did previously and what we’re doing here? Can you give me some examples of the products or processes you handled?

Sample Answer:

Yes, I think there are quite a few similarities. At #, I worked on operational data, especially around inventory and order fulfillment, which required constant coordination with engineering and supply chain teams. I believe this cross-functional setup is similar to how your team works with finance, ops, and engineering. I also used dashboards to share insights, just like your team does with Tableau.

4. Can you give an example of a time you had to verify the authenticity of data—for example, when the data didn’t align with reality, like a mismatch between an inventory list and what’s actually in the warehouse? How did you handle it?

Tip: 현실과 데이터의 불일치 → 확인 절차 → 해결 → 리스크 방지 강조

Sample Answer:

Sure. During one project, our data showed that a specific product had 200 units in stock, but the actual warehouse check revealed only 60.
To investigate, I cross-checked shipment logs and found that a recent bulk return had been mistakenly double-counted.
I worked with the warehouse team to correct the entry in the system and built a simple validation report in Excel that highlights inventory anomalies based on past trends.
This helped catch similar issues early going forward.

회사 M

팀 리더 & 매니저와 인터뷰 정리

1. What is your experience with Power BI? (focus on DAX, data refresh, number of data sources, and cleaning methods)

Tip: DAX 사용 경험, 데이터 정리 방식 (예: Power Query), 여러 소스 연결 경험 강조

Sample Answer:

I’ve used Power BI to build dynamic dashboards pulling from 3 different data sources including SQL Server and Excel. I used Power Query for cleaning and shaping the data, and I regularly used DAX to create calculated columns and measures for custom KPIs. I also scheduled automatic data refreshes via the Power BI service.

2. How did you communicate and manage the whole project? Did you use project tracking tools or meetings?

Tip: Jira, Trello, or Agile 스프린트 사용 경험이 있다면 언급

Sample Answer:

I held weekly check-ins with stakeholders and used Microsoft Teams and OneNote to manage ongoing tasks. For tracking project timelines and deliverables, I used Excel-based Gantt charts and later transitioned to using Jira for better visibility.

3. How do you usually validate that your data is accurate or that what you’re presenting is accurate?

Tip: 데이터 검증 프로세스 (소스 크로스체크, 샘플 확인, 로그 분석 등)

Sample Answer:

I usually start by reconciling key metrics with known reports or source system data. I also use sanity checks, aggregation validation, and often have stakeholders verify small samples for consistency before sharing results.

4. Do you have any experience managing data storage or backend cloud storage?

Tip: Azure, AWS, SharePoint, OneDrive 등 사용 경험 언급

Sample Answer:

Yes, I’ve managed datasets stored in SharePoint and OneDrive, and used those as data sources in Power BI. I’ve also used Azure Blob Storage for archiving and automating data refreshes in dashboards.

5. Do you have experience working in a less structured environment?

Tip: 스타트업이나 초기 프로젝트 경험, 본인이 주도했던 사례 강조

Sample Answer:

Yes, during my internship, documentation and processes were minimal. I took initiative by standardizing reporting templates and setting up data cleaning procedures to bring structure to the workflow.

6. On a scale of 1 to 10, how would you rate your Excel skills?

Tip: 자신 있다면 8~9, 근거와 함께 설명

Sample Answer:

I’d say 8 out of 10. I’m confident using advanced formulas, pivot tables, Power Query, and have experience with VBA scripting for automation.

7. Are you okay with working mainly with Excel and Power BI, not too much more than that?

Tip: 자신 있는 도구를 더 깊이 있게 다루고 싶다는 방향으로 긍정적인 어필

Sample Answer:

Absolutely. I enjoy working with Excel and Power BI and would love the opportunity to deepen my expertise in these tools, especially in areas like advanced DAX and performance optimization.

8. What does your ideal day-to-day look like in a company?

Tip: 팀 협업, 데이터 분석, 회의/보고 균형 있게 언급

Sample Answer:

Ideally, I’d like a day that includes focused time for analysis and dashboard building, some time for team collaboration or standups, and periodic stakeholder check-ins to align on insights and priorities.

9. Can you give an example of when you pulled insights from a dashboard you built and presented them to stakeholders?

Tip: STAR 방식으로 준비

Sample Answer:

Sure! (S) At #, we had a dashboard tracking order delays. (T) My task was to identify patterns in delay causes. (A) I used filters and trend lines in Power BI to isolate major delay types by region. (R) I presented the insights to the supply chain team, which helped them reduce delays by 20% over the next quarter.

회사 M

팀 리더 & 매니저와 인터뷰 정리

1. What kind of products were you supporting there? Was it sales data? High level, general.

Tip: 데이터의 유형과 비즈니스와의 연결을 설명

Sample Answer:

At my previous role, I supported order fulfillment and inventory-related datasets. These included sales orders, shipment timelines, and allocation rules. My work involved analyzing operational delays and building dashboards to support business decisions across supply chain and logistics teams.

 

2. What is your ideal role?

Tip: 회사에 맞춰 협업, 기술, 성장 강조

Sample Answer:

My ideal role involves a mix of technical data work and cross-functional collaboration. I’d love to work with clean architecture for data pipelines, build insightful dashboards, and support stakeholders in making data-driven decisions.

3. What kind of experience do you have with Python?

Tip: 자동화, 데이터 처리, 시각화 등 언급

Sample Answer:

I’ve used Python for data cleaning, transformation, and automation tasks. For example, I built scripts to clean large CSV files, automate Excel report generation, and extract web data using Selenium. I’ve also used pandas and matplotlib for exploratory data analysis.

4. Do you prefer backend data transformation work or frontend dashboard building?

Tip: 둘 다 가능하되 선호도 표현

Sample Answer:

I enjoy both, but if I had to choose, I slightly prefer backend work like cleaning and transforming raw data. That said, I also like visualizing the insights through dashboards and enjoy seeing the impact of my work directly.

5. What’s one project you’re most proud of?

Tip: STAR 방식으로 구조화

Sample Answer:

Sure! (S) At my internship, I noticed that the daily reporting process was manual and took over two hours. (T) I aimed to automate and streamline this. (A) I built a Power BI dashboard with dynamic SQL queries and created an automated data refresh system. (R) The team’s reporting time dropped to under 15 minutes, and it became the primary tool for weekly ops meetings.

6. What is your favourite programming language, tool, or software?

Tip: 실제 경험 기반으로 답변

Sample Answer:

I enjoy working with SQL and Power BI the most. SQL gives me the control to query and shape the data, and Power BI allows me to visualize and communicate insights effectively.

7. When designing pipelines, how do you decide whether to use SQL or Python?

Tip: 상황에 따라 결정하는 로직 설명

Sample Answer:

If the data transformation can be handled efficiently at the database level, I prefer using SQL for performance. But if the logic requires complex manipulation or integration with APIs or file systems, then Python is the better choice. Often I use a combination of both.

8. For your data quality dashboard, what kind of metrics did you set up? How did you collect data for those metrics, and how did it all come together?

Tip: STAR 방식, 구체적인 메트릭 언급

Sample Answer:

(S) At my internship, I was asked to build a data quality dashboard for order data. (T) The goal was to monitor data completeness and consistency. (A) I defined metrics like null value percentage, date mismatches, and duplicate entries. I used SQL queries to collect data and visualized the metrics in Power BI. (R) This dashboard helped the business team quickly detect issues and improve data accuracy over time.

9. In your machine learning projects, how do you separate loading, preprocessing, and modeling?

Tip: 모듈화된 코드 구조 설명

Sample Answer:

I usually structure my ML projects with separate scripts or functions for each step: one for data loading, one for preprocessing (handling nulls, encoding, scaling), and another for modeling. This makes it easier to debug and reuse components across projects.

 

10. How do you handle changes like new columns being added or deleted from the data source? How do you catch and prevent your dashboard from breaking?

Tip: 테스트, 알림 시스템, 문서화 언급

Sample Answer:

I regularly validate the schema and use SQL scripts to check for column changes. In Power BI, I document data models clearly and set up alerts or errors in refresh logs. I also try to make dashboards robust with error-handling measures and test them after any source update.

11. If you could rebuild a project using different tools or technologies, what would you choose and why?

Tip: 성장 지향적 시각으로 답변

Sample Answer:

If I could rebuild my Power BI dashboard, I’d explore using dbt for more scalable transformation and Snowflake for faster querying. This would allow better version control and performance as the dataset grows. I’m always open to adopting newer tools to make my work more efficient.