Data Analyst
Data analysts query, clean and visualise an organisation's data so the people making decisions can see what it shows.
- Median salary*
- $101,400
3.8%vs last year, before tax
- People employed
- 23,300
1.3%vs last year
- Projected growth*
- +18.3%
to 2035
- AI exposure*
- Moderate
- 6 out of 10
- Average hours*
- 40/wk
matches all-jobs average
- Shortage status
- Not in shortage
national
- Data analysts work wherever an organisation collects data, which in practice means government agencies, banks, insurers, hospitals, universities and professional services firms.
- You sit between the people who look after the data and the managers who have to decide something with it, which is what separates this role from data science, where the focus moves to building models.
- No registration or licence is required; most employers ask for a degree, a diploma or a portfolio showing you have handled real data.
How much do data analysts earn?
The median full-time salary for a data analyst is $101,400 per annum, before tax, up $21,000 since 2018.
Day-rate contracting and permanent employment are quoted on different bases, so two figures that look similar may not be. Ask whether superannuation is included, whether the role is fixed-term or ongoing, and how often the salary band is reviewed. Bonuses and penalty rates are uncommon in this work, which means the annual figure is close to the full picture.
What does a data analyst do day to day?
The list below is what fills most weeks; the exact mix shifts with seniority and whatever stage the current work is at.
- Cleaning up messy source data before anyone can trust the numbers that come out of it
- Building and maintaining the dashboards different teams check every week
- Digging into a trend or a drop-off until you can explain why it happened, not just that it did
- Turning a vague question from a manager into a piece of analysis someone can act on
- Presenting findings to people who want the answer rather than the method
What skills do data analysts need?
Employers look for data analysis, statistical modelling, backed by SQL fluency and strong presenting and data storytelling.
Specialist skills
- Data analysis
- Statistical modelling
Software and tools
- SQL
- Power BI
- Tableau
- Excel
- Python
General skills
- Presenting and data storytelling
- Problem solving
- Written communication
Is the job growing?
About 23,300 people work as data analysts in Australia, and employment is projected to grow 18.3% over the decade to 2035. That's healthy, above-average growth, and the role should stay in solid demand.
How do you become a data analyst?
Here's the path most data analysts take, step by step.
- 1Get a qualification that covers statistics and databases
A bachelor degree in data analytics, statistics, economics or computer science is the most common background, held by 52% of the analysts working today. A diploma in data analytics or information technology also gets people into junior roles, particularly with smaller employers.
- 2Learn SQL and one dashboard tool properly
Employers test this in interviews, so practise until you can write a join and build a report without looking things up. Power BI and Tableau both appear in Australian job ads, and Excel is still used almost everywhere.
- 3Build a portfolio of two or three projects
Show the question you started with, the cleaning you had to do and the chart you ended on, using public data if you have no work experience. A hiring manager can tell quickly whether you have actually handled messy data.
- 4Take a first role where data is one element of the work
Reporting analyst, statistical assistant and business support positions all use the same tools and are easier to enter. Graduate programs in government and the large banks are another route, and internships often convert into ongoing work.
- 5Pick an industry and learn its measures
Health, finance, retail and education each have their own definitions and systems, and knowing them is what makes your analysis useful to a team that has to act on it.
Study routes we have checked
Qualifications that are a recognised way into this role, and what else you need.
- Bachelor of Business/Bachelor of Data Science
A recognised route into this role
Complete relevant data-science coursework and projects. Data engineering also requires practical database and programming capability; employer requirements vary.
- Bachelor of Computer Science/Master of Data Science
A recognised route into this role
Complete relevant data-science coursework and projects. Data engineering also requires practical database and programming capability; employer requirements vary.
- Bachelor of Data Science
A recognised route into this role
Complete relevant data-science coursework and projects. Data engineering also requires practical database and programming capability; employer requirements vary.
- Bachelor of Mathematics/Master of Data Science
A recognised route into this role
Complete relevant data-science coursework and projects. Data engineering also requires practical database and programming capability; employer requirements vary.
- Bachelor of Science/Bachelor of Data Science
A recognised route into this role
Complete relevant data-science coursework and projects. Data engineering also requires practical database and programming capability; employer requirements vary.
- Bachelor of Science/Master of Data Science
A recognised route into this role
Complete relevant data-science coursework and projects. Data engineering also requires practical database and programming capability; employer requirements vary.
- Graduate Diploma in Data Science
A recognised route into this role
Complete relevant data-science coursework and projects. Data engineering also requires practical database and programming capability; employer requirements vary.
- Master of Business Analytics
A recognised route into this role
A recognised route into data analysis. Employers usually look for practical skills in tools such as SQL and analysis software alongside the degree.
- Master of Data Science
A recognised route into this role
Covers the analysis skills used in data analyst roles. Employers usually also look for practical experience with analysis tools.
Ready to apply as a data analyst?
Whether you're working toward becoming a data analyst or already are one and want a hand with the next step (sharpening your resume for ATS screening, tightening your cover letter, or knowing what you'll actually be asked at interview), here are examples grounded in this specific role, not generic templates.
What jobs can a data analyst move to?
Moving into Data Scientist typically comes with the biggest pay rise, worth $23,400 a year more on average.
- Data ScientistSuggested move$124,800+$23,400
- Business Intelligence DeveloperSuggested move$111,800+$10,400
- Market ResearcherSuggested move$101,800+$400
- GIS AnalystSuggested move$98,800−$2,600
Thick lines are moves people were recorded making in Jobs and Skills Australia's Data on Occupation Mobility (income tax records, 2011-12 to 2020-21). Thin lines are moves we suggest from skill overlap and entry requirements.
| Move to | Typical pay change | Overlap | Retraining |
|---|---|---|---|
Data Scientist Analysts can move into a scientist position, applying their querying and visualisation skills while building modelling and machine learning expertise. | +$23,400 | 67% | minimal |
Business Intelligence Developer Analysts can move into business intelligence development, using their analytical skills to build reporting solutions, but need further training in information systems and development. | +$10,400 | 21% | reskill |
Market Researcher Analysts can move into market research, using their analysis skills to design surveys and interpret consumer insights with little additional training. | +$400 | 64% | minimal |
GIS Analyst Analysts can become gis analysts, applying their information handling skills to spatial information after a short course in geographic information systems. | −$2,600 | 57% | short course |
Marketing Analyst Analysts can specialise as marketing analysts, applying their analytical skills to customer and campaign information with minimal retraining. | −$7,800 | 67% | minimal |
Moves are chosen from Jobs and Skills Australia's Data on Occupation Mobility, which follows income tax records between 2011-12 and 2020-21, together with entry requirements and skill overlap. A known move is one people were seen making in that data. Pay change compares median full-time pay for the two roles.
Who works as a data analyst?
The typical data analyst is 36 years old; 58% are men, 86% work full-time, and full-timers average 40 hours a week.
- 36
- Median age
- 42%
- Female share
- 86%
- Full-time
- +0h
- vs all-jobs avg
What's it like being a data analyst?
Most weeks mix routine reporting with one or two questions nobody has answered before, and you'll spend longer than you expect cleaning data before any of it holds up. Requests arrive from several teams at once, so deciding what to drop when two deadlines clash is a real skill. If tracing a strange number back to its cause is satisfying to you, this work holds up well over years; if you need something finished and visible at the end of each day, the screen time gets old.
What people like
- Finding the answer nobody had. You're the person who works out why sales fell in March, and the explanation usually arrives as one clear chart or figure.
- Skills that carry between industries. SQL and a dashboard tool work the same in a hospital, a bank and a university, so changing sectors doesn't mean starting again.
- Hybrid work and a calendar you control. Many analyst roles are hybrid, and outside month-end and board deadlines you largely set your own hours.
- A view of how the organisation really works. You see the claims, enrolment and sales data behind the strategy papers, which builds useful business knowledge quickly.
What people find hard
- Data quality is never finished. Source systems change, fields get renamed and someone's manual fix disappears, so work you completed last quarter can break without warning.
- Waiting on access and answers. You often can't start until IT grants permissions or a business team replies to a question, and that delay isn't yours to fix.
- Requests arrive faster than you can answer them. Someone wants a number within the hour while you're mid-way through something bigger, and you learn to push back on the least urgent ones.
- Reporting cycles bunch together. Month-end, budget season and board papers land in the same few weeks, and the days before each deadline run longer than usual.
Based on our synthesis of professional-body surveys and public accounts of the role, not first-person verified reviews.
Which industries employ data analysts?
Professional, Scientific and Technical Services employs the largest share of data analysts, followed by Financial and Insurance Services.
Top employing industries
- 1Professional, Scientific and Technical Services
- 2Financial and Insurance Services
- 3Public Administration and Safety
- 4Health Care and Social Assistance
- 5Education and Training
Ranked by employment share; the source doesn't publish an exact percentage per industry.
| Bachelor degree | 52% | |
|---|---|---|
| Postgraduate | 26% | |
| Diploma / Advanced Diploma | 13% | |
| Other | 9% |
Will AI replace data analysts?
Moderate exposure. Not replaced, but changed. AI is taking on some tasks and the rest of the job shifts around them.
AI already writes a fair share of the code and produces the first draft of a chart, so routine querying and formatting are exposed. What keeps the exposure moderate is everything around them: deciding which question matters, judging whether a result is plausible, and getting a team to change a decision. Lean into checking and correcting what these tools produce, and build enough industry knowledge to know when a number looks wrong.
How a typical week splits
- Writing and checking SQL queries30% of the week
Assistants draft the joins and filters quickly, but you still have to confirm the output matches a source you trust.
- Building dashboards and recurring reports25% of the week
Power BI and Tableau now suggest visuals and generate measures, which speeds up the first version and leaves the definitions and layout to you.
- Investigating why a number moved20% of the week
Software will flag the anomaly in a series; explaining it means checking a pricing change, a system migration or a batch of late claims with the people involved.
- Establishing what a team actually needs25% of the week
A request for churn numbers often means something narrower, and pinning that down depends on understanding the business.
How we work this out
We break each job into its main tasks, estimate the share of a typical week each one takes, and judge how far current AI and automation tools reach into it. The score out of 10 starts from the job's overall rating (low is 1 to 3, moderate 4 to 6, high 7 to 10) and the task split places it within that range. Source: Career Tips analysis of each role's main tasks.
Common questions about becoming a data analyst
Straight answers to the questions people ask most.
How much do data analysts earn in Australia?
$101,400 per year before tax for full-time work. Banks, insurers and technology employers tend to pay above universities and government agencies, and contract work is usually quoted as a day rate. If you're negotiating, ask what the band is for the level above yours, since promotion is the quickest way the figure changes.
How do I become a data analyst?
Learn SQL and one dashboard tool well enough to use them unaided, then build two or three projects on data you can explain in an interview. Employers hiring juniors care about whether you have handled messy data, though larger organisations often filter on a bachelor degree. A diploma plus a portfolio is a realistic path in, particularly with smaller employers.
Are data analysts in demand?
Data analysts are currently not in shortage, and employment is projected to grow 18.3% over the decade to 2035 over the decade. The openings sit across government, health, finance and education, and almost all of them expect you to have the tools before you start. Check which industries in your city hire analysts and aim there.
Will AI replace data analysts?
Tools such as Copilot now write a good share of the SQL and produce the first version of a chart, which shortens the time between a question arriving and a draft answer. What they don't do is decide which question is worth answering, notice that a number looks wrong, or persuade a manager to act on the finding. If you're coming into the role now, practise checking what a model returns against source systems, because that judgement is worth more as more drafting is automated.
What jobs can a data analyst move into?
Data scientists earn $23,400 more at the median, and the move builds on the same querying and visualisation skills with extra study in modelling and machine learning. Marketing analysts and market researchers use the same tools on campaign and customer information, so the step across is short. A GIS analyst role means learning geographic information systems and mapping software first.
Do data analysts need to be good at maths?
You need comfort with statistics and percentages, not advanced mathematics. Querying, cleaning and explaining take up the bulk of your time, and the harder calculations are handled by the tools. If you avoided maths at school, an introductory statistics unit closes the gap quickly.
Related roles
- Data Scientist
- Marketing Analyst
- Market Researcher
- GIS Analyst
- Business Intelligence Developer
- Statistical Assistant
Not sure this is you? Take the career quiz and get a ranked shortlist of roles that fit how you like to work.
Career advice
- Problem solving skillsProblem solving skills are what let you notice that something at work isn't going to plan, work out why, choose a fix and check that it worked.
- How to change careers, and which moves are realisticData on 1,573 career moves across 350 Australian occupations shows 63.3% need no more than a short course, though skill overlap alone won't tell you which ones. Six worked examples, and how to check your own move.
- Skills to put on your resume (with skills finder)A resume skills section built for the job you're applying for. Search your occupation to see the specialist skills, tools and general skills it calls for, with worked examples and what to write if you have no work history yet.