Data Analyst
Data analysts query, clean and visualise an organisation's data so the people running it can see what is actually happening.
- 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
- automation risk
- Average hours*
- 40/wk
matches all-jobs average
- Shortage status*
- 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. The role sits between the people who hold the data and the managers who have to decide something with it, and that is what separates it from data science, where the focus shifts to building models. Most of the day is spent in SQL, a spreadsheet or a dashboard tool rather than on advanced statistics.
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.
Pay moves with the sector and the size of the data function behind you: banks, insurers and large consultancies generally pay above the public sector, where enterprise agreements set the bands. Contract and day-rate work through a labour hire firm can pay more than a permanent role with the same title, though it comes without paid leave or job security. Specialising in a platform employers are actively hiring for, or moving from reporting into modelling, tends to shift the figure more than years of service do.
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 business question 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.
- 1Build the analytical foundation
A degree in statistics, mathematics, computer science, information systems or business analytics covers the ground most employers expect. A diploma through TAFE is a realistic alternative for someone who wants to start sooner, particularly in government and health reporting teams.
- 2Learn SQL and a visualisation tool
SQL is the common language of the job, and Power BI or Tableau is where most Australian workplaces visualise, so hands-on practice with both matters more at interview than another certificate. Excel and increasingly Python sit alongside them.
- 3Get a first role where data is the job
Titles vary widely: reporting analyst, insights analyst, data officer, business analyst. Government graduate programs and the large banks and insurers recruit juniors in cohorts, and for career changers an internal move from a role that already touches the data is a common way in.
- 4Fill gaps with a short course or a portfolio
If your degree is in another field, a graduate certificate in data analytics or a short course in SQL and a dashboard tool gives you something to show. Two or three analyses built on public data are one way to prove the skills without work experience.
- 5Specialise once you are working
Experience with a particular platform, a sector's data or a modelling technique is what opens the next move. Data science, marketing analysis and business intelligence development all draw from this role, and each asks for a different extra skill.
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.
| 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 | 37% | 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?
The job has a steady rhythm of questions coming in and answers going out, and much of the week is spent alone with the data before you surface to explain it. The pressure sits in the explaining, because a manager who has to make a call on your number will ask what it means and whether you trust it. It suits someone who likes untangling a messy question, is content to spend a few hours in a query editor, and is comfortable presenting what they found to people who will act on it.
What people like
- The answer is usually discoverable. A question arrives fuzzy and you work through the data until it makes sense. The moment a chart lines up with what someone suspected is the reward the job runs on.
- Your work gets used. A dashboard you build on Tuesday can be shaping a decision on Thursday, and people come back to it every week. That feedback loop is faster than in jobs where the output sits in a drawer.
- The skills travel. SQL and a visualisation tool work much the same way in a bank, a hospital or a government department, so you can change sectors without starting over.
- Autonomy over method. You often decide how to approach a question, which tools to use and how to present the result, even when someone else set the question.
What people find hard
- Cleaning takes longer than analysing. Source data arrives with duplicates, inconsistent formats and missing fields, and getting it into a usable state can eat most of the time you were given for the whole job.
- Requests arrive with no context. 'Can you look at why sales dropped?' with no period, region or definition of sales is a common starting point, so the first part of the task is working out what was actually meant.
- You are often last in the chain. Your analysis feeds a decision someone else makes, and you may never hear how it turned out.
- The reporting cycle never stops. Weekly and monthly dashboards have to go out on time whether or not anything interesting has changed, and that part of the work is repetitive.
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?
The job sits in the middle: AI writes a first draft of SQL, generates chart code and produces quick summaries of a dataset, which removes some of the mechanical work at the front end of a task. What it does not do is work out which question matters, judge whether a number reflects reality, or explain a result to a manager who has to act on it. Analysts who use these tools well spend more of the week on interpretation and less on typing.
Share of typical working time by exposure level
- Cleaning and reconciling source dataTools flag duplicates, odd date formats and missing fields, but someone who knows the business still has to decide what a blank value actually means and which fix is right.30%moderate
- Writing queries to pull data togetherAn assistant can turn a plain-English request into a working SQL statement in seconds, which speeds up the first attempt, but checking that the joins and filters return the right population is still on you.25%high
- Building and updating dashboardsVisualisation platforms suggest chart types and layouts quickly, while choosing the measure that answers the team's real question is the part that takes experience.25%moderate
- Interpreting findings and briefing the people who askedExplaining why a number moved, what it does not tell you and what to do next happens in conversation with managers, and that translation is the hardest part to automate.20%low
Common questions about becoming a data analyst
Straight answers to the questions people ask most.
How much do data analysts earn in Australia?
Full-time data analysts earn a median of $101,400 per year before tax. It is a median, so half earn more and half earn less, and the figure moves most with your sector, whether you are permanent or contracting, and how specialised your tool skills are.
How do I become a data analyst?
Most people come in through a degree in statistics, mathematics, computer science, information systems or business analytics, then build the tool skills employers ask for. A diploma or graduate certificate works for career changers, and short courses in SQL plus a visualisation platform can get you to interview if you have a portfolio to show. Analysts also step across from adjacent work such as reporting, marketing analysis or statistical assistance, where the transition is close.
Are data analysts in demand?
Data analysts are currently in shortage nationally, and employment is projected to grow 18.3% over the decade to 2035. Openings appear across government, finance, health, education and professional services because organisations have collected data faster than they have hired people to interpret it. For someone entering now, the practical move is to demonstrate working tool skills, since employers hiring at junior level weigh a portfolio or a test task heavily.
Will AI replace data analysts?
AI tools now draft SQL, generate chart code and summarise a dataset, so the mechanical parts of the job are exposed. What stays with the analyst is deciding which question is worth answering, judging whether a number reflects reality, and explaining a result to the people who will act on it.
What can a data analyst move into?
Data science is one destination, where pay is $23,400 more and your querying and visualisation skills carry across while you build modelling and machine learning experience. Analysts also move sideways into marketing analysis, applying the same methods to campaign and customer data, or into business intelligence development, which means building reporting solutions and usually needs further training in information systems and development.
What hours do data analysts work?
Full-time data analysts average 40 hours a week, and 86% of people in the role work full time. The work runs on ordinary office hours, with extra time around month end or when a major reporting deadline lands.
Related roles
- Data Scientist
- Marketing Analyst
- Market Researcher
- GIS Analyst
- Business Intelligence Developer
- Statistical Assistant
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