How to Write a CV That Doesn’t Suck (For People in Data & Tech)
Why this Matters
Your CV is like the Passport for your Career.
Except a Passport lasts for 10 years and you're stuck with that terrible photo from 2017.
With a CV, you get to retake that "photo" and change the details at any time.
Some people are better at getting that perfect snapshot than others.
And that puts them at an advantage in the job search.
Hard to get that picture looking good, right? Mr Bean struggles too.
CVs are by nature a reflection of one's skills & experience.
When condensing several years of experience into 2-pages, there is a lot that can get lost in translation and it is nigh on impossible to do perfectly.
If CVs were perfect there would be no need for interviews.
Alas, we don't live in a utopia where this is the case.
A CV provides an indicator for whether a further discussion should be had.
So putting the best foot forward can be the difference between rejection and success.
Rachel Tran and I look at at least 10+ CVs per day, sometimes more, and here are some key areas we look for. I'm writing this to help with those that don't know where to start when it comes to writing data & technology profiles.
Structure
A CV that's uniformly laid out helps us A LOT in being able to decipher value and best fit for a specific role. There's some contention about what is the best approach but at a personal preference level, I've found below sections work well together:
Summary: Start with a short paragraph that tells us who you are and where you're headed. Share a bit about your background, what drives you and your career aspirations. Keep it human and add a bit of personal flavour. AI is all the rage, so being human makes a huge difference (but don't go so far as to throuw in spelling errors).
Education: List your formal tertiary qualifications here e.g. university. If you absolutely smashed it and got a high CWA (course-weighted average) and the Vice-Chancellor's Excellence Award, put this in too. But if your CWA is nothing to brag about...then don't worry, no need to put that down (you still got the degree right?). My CWA is nothing to be proud of...
Certificates: In data and tech, certs actually matter, especially vendor-specific ones like Microsoft, AWS, Databricks and Snowflake. This is where you drop them in. If they’re current and relevant, include them. If they expired in 2016, maybe let those rest in peace.
Technology: I'm a big fan of seeing a list of different programming languages, tools and technologies used. A clear list of what you’ve worked with helps us connect the dots quickly. Bonus points if you get specifics e.g., Python (Pandas, NumPy, Matplotlib), Azure (Data Factory, Synapse, ADLS). Not just vague tool names thrown in for SEO.
Experience: aka, The Big Kahuna - what will probably make up 50% - 70% of your CV. For each role, link your responsibilities to the technologies you’ve listed above. Show us how you actually used them. What did you deliver? What changed because of your work? If you worked on an ADF to Databricks migration or helped move the business from Tableau to Power BI, tell us. And please… don’t just copy/paste “increased efficiency by 743%” because you saw someone else do it. If it’s real, share it. If not, focus on impact.
Extra-curricular: Add a bit of flavour here. If there’s something interesting about you that a hiring manager might enjoy, chuck it in. Love gaming? Cool, what do you play? Into yoga? Awesome, where do you practice? You can also list things like internships, side projects, awards volunteering. Basically anything that shows initiative or personality.
Do's
Tailor your CV to the job: One-size-fits-all is a myth. I'd recommend re-writing your summary for each role or even having a big master resume of your experience that you cut out the relevant projects for and condense into two pages for each role. for ponchos, not resumes.
Reference your tools in your experience: Don’t list Snowflake as a technology you know then never reference it in your experience...that gives me nothing to work and it can seem like you're making stuff up.
Keep formatting consistent: Look this is basic but very obvious if not done correctly. Fonts, spacing, dates... it all matters. You don’t want the CV equivalent of a desktop with 100 icons.
Include real outcomes: If your work made something faster, clearer or easier, say so (no need to fake the % though - we’ll get to that).
Stick to 2 pages: In Australia, 2 pages is perfect for a CV. Anything less, I've found that there's often a lack of detail to make decisions. Especially if you're under 10 years into your career, 2 pages is fine.
Don'ts
Don’t list every tech tool ever invented: You used MySQL once in uni? Maybe leave it off unless it’s still relevant. Sometimes graduate CVs have more technology on their profiles than people with 5 years industry experience.
Don’t make up stats: "Increased pipeline efficiency by 847%"...mate, no you didn’t. Keep it real.
Don’t write in third person: There is some debate about third or first person. First person or implied first person is fine. It's not a dealbreaker, can swing both ways.
Don’t AI-generate the whole thing and call it done: You can use it to kickstart ideas, sure. But edit it so it sounds like you. If you're using AI then it'll sound generic like the other 100 applicants. Not a way to stand out.
Don’t use passive clichés: “Team player,” “go-getter,” “detail-oriented”... prove it with your experience instead.
Don’t forget to proofread: Typos and grammar mistakes are like bugs. The CV won't run and compile with the reader - damaging your credibilty.
Refrain from doing this.
How to Stand Out
Alright, let’s be honest...most CVs kinda blend together after you’ve looked at a few dozen in a row. So how do you make yours stand out without using Comic Sans or adding “Data Guru” to your job title?
Here’s the lowdown:
Tell a story (just not a novel) Your CV shouldn’t read like an essay, it should give us a feel for what you’re about. What you’ve tackled. What you’ve delivered. What kind of environments you thrive in. Recruiters and hiring managers aren’t just scanning for keyword, they’re scanning for signs of life in what sometimes feels like a desert.
Use real language, not buzzwords If your experience section sounds like:
"Strategically leveraged cross-functional synergies to disrupt enterprise-grade paradigms..."
No one’s buying it. Just tell us what you did. Clear, simple, human language wins every time.
Make your tech stack useful, not overwhelming Yes, it’s great that you’ve touched 58 different tools, but maybe don’t list every one since 2011. Prioritise what’s current, what you’ve used deeply and what’s relevant to the roles you’re targeting. Keep the rest in your back pocket for interviews.
It's Not Just Your CV That Gets Looked At
In data and tech especially, a strong CV is only half the battle. Your online presence makes a big difference. With candidates we submit to clients, I often share LinkedIn profiles now too!
LinkedIn: Still using a blurry selfie from the Gala Dinner you went to? Time to freshen it up. A sharp, recent photo and an up-to-date profile go a long way. Hot tip: Make your “About” section conversational and relevant, not just a copy-paste of your CV.
GitHub (if relevant): If you’re a developer, engineer or data scientist and you’ve got a GitHub Hiring managers will look. Don’t panic if it’s not a perfectly curated portfolio, but if it exists, make sure it reflects you and not just forks from tutorials.
Certifications & badges: Got Microsoft, AWS, or Databricks certs? Chuck ‘em on LinkedIn and your CV. It shows commitment and gives weight to your skills. It adds social proof.
Public projects or blogs Got an article on cleaning dirty data with Pandas? A Power BI dashboard you’re proud of? Share it! It builds trust and shows you’re active in the space.
One Last Thing...
Don't wing it and start with an empty word doc.
Just like coding, you never start with a blank file, use templates. Get peer-reviewed. And create multiple iterations.
Start with a template: There are a tonne of good ones out there (we’ve even got a few we can send you). Let structure do the heavy lifting so you can focus on content.
Get feedback early: Ask someone who actually reads CVs to have a look. You don’t need to wait until it’s “perfect.”
Iterate: Treat your CV like a project. Build. Test. Improve. You wouldn’t push untested code to prod, so don't do it with your CV.
Don’t let “not knowing where to start” hold you back. You’ve got good stories. You’ve delivered real value. Your CV just needs to reflect that.
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Thanks, Douglas Robertson from DR Analytics Recruitment
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