re: I'm a New Zealand based Data Analyst and Career Switcher, Ask Me Anything! VIEW POST


What are your tips on landing the first job as a data analyst?


If you've gone through some beginner SQL online training like CodeAcademy or PluralSight now is the time to start applying for junior roles.

When I'm part of the hiring process for a junior analyst I would rather see an enthusiastic candidate with solid basic skills and people skills rather than someone who has done more and more online training.

Once you are in your first job the learning curve ramps up and you are faced with real-world issues - dirty data, complex data models, legacy issues that mean that the data is not always in the pristine format of the online tutorials. The sooner you get into the real world the better.

You are going to learn so much more on the job than going through online tutorials, so once you've got the basics down, get interviewing :)


Thanks for your advice :D Usually for a junior analyst role, what are some interview questions recruiter would potentially ask? Could you give some examples? I really want to know the specifics.

Sure thing. Here are some examples of what I'd be asking a junior - intermediate analyst:

Business and Career

  • What unique skills you think can you add on to our team?

  • Where do you sit on the Data Analyst (business analysis, lower-end technical) ←→ Data Science scale (mathematics, statistics, programming, technical)

  • What do you actively do to keep your technical skills up to date?

  • Describe an example you worked on where you played an active role in solving a business problem through an innovative approach.

Understanding Requirements

  • Can you briefly explain how you go about understanding requirements? Do you follow a specific process or framework?

  • Give an example of a particularly difficult situation where you successfully delivered a solution.

  • Can you provide an example where you had a customer extend the scope of work after the scoping had been completed and signed off? If so, what was the situation, how did you handle it, what was the result?

  • Give an example of where you struggled and it wasn’t successful

  • While most of our customers are great, we do often have to set boundaries and expectations around tasks, can you please provide an example of a time where you had to manage a strong willed stakeholder, how did you go about managing expectations while protecting the relationship(s)?

Data collection, Data exploration, Data preparation, Modelling

  • Is more data always better? Do you prefer raw or enriched (e.g. Data Warehouse) data more - why?

  • What're the largest datasets you have had to use? What types of systems did these come from e.g. financial, customer, usage, operational etc.

  • Describe the different types of data formats you have worked with.

Cleanse, Shape, Transform and Enrich

  • When dealing with ambiguity and data quality challenges what do you do? What level of accuracy is enough?

  • List out some of the best practices for data cleaning, especially for large datasets?

  • Give an example of when you proposed changes to improve data reliability and quality. Did these changes end up being implemented? If not, why not?

Data Analytics

  • Which tools are you familiar with? What’s your preference?

  • Describe an example of a complex analysis that you ran that you are particularly proud of, your approach and the insights gained

  • Give a couple of examples where you had to create advanced metrics - what were these and why were they advanced?

  • What’s the most advanced data analysis techniques have you applied to determine one or more insights?


  • What tools have you used to publish data to end users?

  • Do you have any examples of visualisations/charts that you thought made a big difference (beyond the column/bar, line, geospatial scatterplot etc)?

  • Have you ever used D3 or other javascript based visualisations?

  • What form of supporting user help would you include?

  • Have you had to deal with data that is inappropriate to share with the intended audience? How do you determine this?

  • Have you ever increased the value of a dataset/dashboard after you have published the dataset, say a few months later?

That's really helpful! I really appreciate your advice.

Could I ask one more question?

When you were applying for a data analyst job, did you go through a standard process? How could you stand out of the large pool of applicants applying for the same role?

Thank you very much!

No worries :)

I went through the standard process for a DA role here in NZ. This usually consists of a screening interview over the phone from HR/recruiter, then a technical interview/take-home test, then an interview for cultural fit.

Technical interviews

These are more about talking through how and why you would do something or which approach you would take, rather than the 'whiteboard' interview that the Devs here talk about.

The generally cover:

  • SQL Skills
  • Requirements gathering
  • Visualisations

To prepare I would recommend knowing the projects you have worked on really well:

  • what went right,
  • what went wrong,
  • how you would improve,
  • the SQL skills you used in your code,
  • the way you visualised the results set at the end,
  • how you would communicate to the final stakeholder

SQL Skills

  • The testing site we use at my workplace is Hackerrank, I'd recommend giving it a go to test your skills - hackerrank.com/domains/sql

  • I'd also recommend downloading the free version of SQL Server and SQL Server Management Studio (SSMS) if you have only used a browser based tutorial so far.

Download SQL Server - this is the query engine
Download SSMS - this is the UI you interact with
Download and restore the backup of the AdventureWorks DB
Work through some of the examples

Good luck in your preparation

Your recommendations are extremely valuable! Thank you so muchhh!

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