Brick by Brick: A Guide for Breaking into Data

You are Most Qualified to Help the Person You Used to Be - Ed Mylett

I've been the person trying to break into the data industry...

And succeeded in becoming a Data Analyst in 2022.

Here's my guide looking back connecting the dots.

Begin Here

It's graduation season.

I run a recruitment agency specialised in the data & analytics field - DR Analytics Recruitment

Graduates often reach out to me looking for work.

Unfortunately, as an agency, our clients engage us typically for more senior experienced roles.

It is not like I'm holding 10x graduate positions hostage - it's just not a space we work in.

That being said - I know the industry and the challenge of breaking in.

This article is a helping hand for what I would say to someone that has just graduated or has been upskilling in data and is looking to make a career switch.

The Philosophy - Brick by Brick

The strongest way to view your career and job search is as if you're building a wall.

No single brick makes a perfect wall; you just keep laying them. Some bricks are bigger than others, for example a degree, but that doesn't make up the whole wall. Companies hiring will assess your whole wall, and see if they want to add it to their kingdom. All that is within your power, is to keep laying bricks and making the wall stronger.

Education is just one brick. Seeing your career as a wall removes the binary thinking of 'am I good enough?' and shifts it to 'I'm simply laying more bricks' This is the growth mindset (Carol Dweck) that people often refer to.

Some key bricks you should be aware of and start laying:

• Network - who you know.

• Projects - what you've done.

• Sales - how you present yourself.

• Experience - past bricks from your life.

Let's go through them and how you can start building your wall more.

Network - Who You Know

We've all heard the saying "Your network is your net worth".

But what does this really mean and how do you build it?

Story Time:

So my Barista was my network to break into data & analytics - not the traditional way people see network.

This relationship had been built over hundreds of coffees and small interactions to the point where the Barista liked, knew and could confidently refer me.

The same applies to any person and their network.

It's not necessarily the traditional networking events you need to go to, but share your dream and what you're doing with those around you and there may be an introduction to be made!

Now, if you're looking to network with your peers I'd suggest events in the data, analytics and AI space across your local area. The mindset of going into these is learning and helping others not getting a job offer on the spot; learn what tools are popular, how other people broke in and be interested in the field!

If you're in Perth, join these meetups:

• Perth Microsoft Data & Analytics User Groups

• Perth Data Engineering Meetup

• Perth Modern Excel & Power Bi User Group

• AWS User Group

• Databricks User Group

• Python WA

• Industry Inner Join

• DAMA

Go with curiousity and a mindset to learn - seek to become a regular rather than tick a box.

If you push it, you should be able to attend one per week!

(I'm at most events so would be great to see you out there)

Projects - Get Busy

If your GitHub contributions look like this, your career will be fine:

This is a little extreme, but consistent GitHub contributions indicates a few things that can't be shared in your CV:

1. Interest in learning and your craft

2. Love for what you do

3. Consistency

A common question I get is "what projects should I do for employers?"

There's two ways to look at this. You can (1) pick industry specific topics e.g. mining or energy and build a pipeline and visualise the data or (2) just do what interests you and you love.

If you struggle with projects because you don't like coding or learning...then pick a different field.

Some example project portfolios that I've seen:

• https://github.com/BunningsWarehouseOfficial

• https://github.com/RashidCodes

• https://github.com/davidptsmith

When you complete projects, let the world know about it! That leads into sales

Sales - The Dirty Word

This may make people uncomfortable as a corporate professional in data, analytics and AI...

Sales is important, but not in the pushy carsalesman sense.

With employment, you're selling your time and skills to an employer.

You need to be able to effectively articulate your skills, knowledge and value in a way an employer can understand. Especially in a technical field, this is paramount as interviewers may be non-technical.

This does not mean making things up. It means conveying your capability clearly and not short-selling yourself.

You could be extremely capable in Power BI and make beautiful reports however if a prospective employer never gets to see any, the chance of them understanding what you can do is very low.

Here's what to consider:

/ CV - clear, concise, follows best practices, not too cramped, outlines your capability.

/ LinkedIn - a landing page for your skills, check out this profile for an example.

/ GitHub - a landing page for your skills, check out GitHub profiles above for reference.

/ Verbal - hhave examples of your work and an elevator pitch ready. A good elevator pitch template is: Name, Same, Fame, Aim, Game (watch this video: 22:48)

Experience - Everyone Has It

"But Doug, I have no industry experience so how is this relevant to me?"

Stop. Everyone has valuable life experience.

Before starting in recruitment, I worked in a cafe which was foundational people skills required for the recruitment role. Then when interviewing to become a Data Analyst, my communication was the key skill that got me in.

Some examples:

Hospitality and retail build communication, problem-solving, and time management skills all crucial for data roles. Adjusting staffing based on sales trends is data-driven decision-making, isn't it?

Admin and office roles involve data entry, automation and reporting, all of which translate to analytics. Automating a manual report in Excel is already applying data skills.

Finance and accounting rely on numbers, forecasting and reporting - essential basics for analytics. Creating dashboards to track expenses is a direct data application.

Logistics and operations involve process optimisation, inventory management and performance tracking. Reducing waste through better forecasting is data analytics in action.

Even teaching and coaching require analytical thinking. Explaining complex topics mirrors presenting insights to non-technical stakeholders.

Rather than focusing on job titles, identify where you’ve worked with numbers, improved processes, or made data-driven decisions. Your experience is more relevant than you think.

The Landscape

Don’t fall into the trap of thinking that a "Data Analyst" job is the only way in. These roles are often the most competitive because they’re seen as the obvious entry point. But there are plenty of other paths into the data industry, and the trick is to spread your net wide.

Here’s how to think about it:

Graduate Programs – The Structured Route

Large companies often run structured graduate programs in data, analytics and tech. These are great if you want formal training, mentorship and a defined career path. The downside? They’re highly competitive and usually follow strict application cycles. If you’re interested, research them early and apply well before graduation. Some major players with data-focused grad programs include:

• Big 4 Consulting Firms (Deloitte, PwC, EY, KPMG) – Heavy on client work, fast-paced learning.

• Banks & Financial Services (CBA, ANZ, Westpac, NAB, Macquarie) – Strong focus on risk, fraud detection, customer analytics.

• Tech Giants (Google, Microsoft, Amazon, Atlassian, Canva) – Data-driven at their core, but tough to get into.

• Government & Public Sector – Stable jobs, big datasets and an opportunity to work on projects that impact society.

Tip: Many of these programs don’t advertise as “Data Analyst” roles – look for titles like "Data Graduate," "Business Intelligence Graduate" or "Technology Graduate."

Mid-Tier & Boutique Consultancies – The Hidden Goldmine

You might not have heard of them, but mid-sized consultancies are some of the best places to break in. They do data & analytics work for clients without the same level of competition as the Big 4. These firms often work on a wide variety of projects, meaning you’ll get experience across multiple industries.

Examples include:

• Specialist Data & AI Consultancies (e.g., Mantel Group, Servian, Data#3, Quantium)

• Broader IT & Business Consulting Firms (e.g., Accenture, CGI, DXC Technology, Avanade)

Why consider them?

• Less competition than graduate programs.

• More hands-on work early in your career.

• Exposure to different industries and tools.

Small-Medium Businesses (SMBs) – The Underrated Entry Point

Most people ignore SMBs when job hunting, which is a big mistake. These companies might not have massive data teams, but that’s actually a good thing - you’ll wear multiple hats, gain a variety of experience and quickly become a valuable asset.

Think of:

• Startups – Fast-paced, lots of responsibility, but often chaotic.

• Retail, Healthcare, Logistics, Manufacturing – Data roles exist here, but they’re often called something different (e.g., “Reporting Analyst” or “Business Analyst”).

• Nonprofits & Government Agencies – They need data skills too and are often more open to hiring career changers.

The key is not to get stuck on job titles. Instead, look at the job description and see if it involves working with data. If it does, it could be a great stepping stone.

Entry Points Beyond Data Analyst – Keep an Open Mind

If you’re struggling to land a Data Analyst role, consider these adjacent positions:

• Business Analyst, Reporting Analyst, .Marketing Analyst. Operations Analyst. Finance Analyst

Once you’re in, you can always pivot towards the data job you really want. The first step is just getting your foot in the door.

Easter Egg

If you made it this far, thanks for your persistence and here's an opportunity.

DR Analytics Recruitment is likely (not 100% confirmed) hiring for an Entry Level Data Analyst role in April/May 2025. The Hiring Manager specifically needs these skills:

• Growth mindset and positive energy, passionate about data and what it can do for business.

• 50% speaking to business stakeholders for requirements, 50% delivering data solutions

• Basic understanding of SQL and how businesses operate.

• $70 000 - $80 000 + super

You can submit your application here which will be reviewed closer to the data. We will not be interviewing yet or accepting direct message applications. If you've read this far, include 'Hi Doug' in your CV. Apply here.

Conclusion

It's not about making giant leaps all at once.

It’s about steady, consistent progress.

Laying one brick at a time.

Good luck building your wall.

- Doug