Data analyst salary in Melbourne and the national full-time average
If you're a data analyst in Melbourne, you probably want to know how your pay stacks up against the Australian full-time average. The site's line is set at the national full-time adult ordinary-time average: $2,083.70 per week, or about $108,352 per year (ABS Average Weekly Earnings, May 2026). This is the benchmark we use to show where any salary sits.
But the Australian Bureau of Statistics does not publish a specific salary for data analysts in Melbourne. That means we can't give you an exact figure. Instead, we can use the data that is available to give you a sense of the market.
State and territory averages
Victoria's full-time adult average weekly ordinary time earnings are $2,041.10 per week, or about $106,137 per year. That's slightly below the national average. Other states vary: New South Wales is $109,658, Queensland $106,064, Western Australia $115,825, and the ACT $119,090. You can see all state figures on our states and territories page.
Industry averages
Data analysts often work in the professional, scientific and technical services industry. The ABS reports that full-time adult ordinary time earnings in that industry are $2,389.60 per week, or about $124,259 per year. That's well above the national average. Other relevant industries include information media and telecommunications, financial and insurance services, and public administration. Each has its own average.
Medians vs averages
Remember that the figures above are averages, not medians. The national full-time median earnings (from ABS Employee Earnings, August 2025) are about $90,532 per year. The all-employees median (including part-time) is about $74,100. Medians can be more representative of typical pay, especially in fields with a wide range of salaries. You can explore job medians on our site.
Using the site's tools
To see where your salary sits, you can place a salary on the line. Enter your yearly pre-tax pay, and the tool will show you the weekly and hourly equivalents (based on a 38-hour week) and the distance from the national full-time average. It also shows where you fall relative to the minimum wage and the tax brackets.
Minimum wage and awards
The national minimum wage from 1 July 2026 is $26.44 per hour, $1,004.90 per week, or $52,255 per year on 38 hours. Award minimums rose by 4.75% from that date. Data analysts may be covered by the Professional Employees Award 2020, which has higher minimum rates for degree-qualified professionals. Check Fair Work for the correct classification.
Tax considerations
For 2026–27, resident tax rates are: nil on the first $18,200, 15% on income up to $45,000, 30% up to $135,000, 37% up to $190,000, and 45% above that. The Medicare levy adds 2% (before any reductions). A data analyst earning around the Victorian average of $106,137 would be in the 30% bracket plus Medicare, so the marginal tax rate is 32%.
How the figures are set
The national full-time average comes from the ABS Average Weekly Earnings survey, released twice a year (May and November). The latest is May 2026. Medians come from the ABS Employee Earnings and Hours survey, released annually (most recently August 2025). The minimum wage is set by Fair Work. For more detail, see how the figures are set.
What if you earn more or less?
If your data analyst salary in Melbourne is above $108,352, you're earning more than the national full-time average. If it's below, you're below the line. But remember that averages can be pulled up by high earners. The median gives a better sense of the middle. Use our tools to compare your pay to both.
Summary
While there's no official data analyst salary for Melbourne, you can benchmark your pay against the Victorian average ($106,137), the professional services industry average ($124,259), and the national full-time average ($108,352). The site's line is the national average, and you can place your salary on the line to see the comparison instantly.
For more context, explore our industry medians and job medians pages. And remember, the best salary data is specific to your role, experience, and employer. Use these benchmarks as a starting point.