Data analyst job description

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What does a data analyst do? ​

Data is everywhere and in recent years, the amount of data being generated and collected by businesses has grown exponentially in recent years. The arrival of big data - large volumes of varied data generated at velocity - has created new opportunities for companies to generate valuable insights to inform their decision making. 

This in turn has resulted in a huge uplift in demand for skilled data analysts across the full spectrum of industries and professions. Data analysts and data scientists are highly sought after and frequently feature on lists of the most in-demand jobs and jobs of the future.

At a fundamental level, a data analyst gathers data from various sources and then reviews and interprets it using data analysis tools to provide meaningful information and insights to help businesses make better-informed decisions. This could be decisions about any aspect of business, for example investments, cost-savings, pricing, hiring, operations or scheduling - all of which can help to create a competitive advantage in the marketplace.

Data analyst responsibilities

  • Identifying data sources
  • Collecting data
  • Sourcing missing data
  • Organising data in to usable formats
  • Analysing data to find answers to specific questions
  • Setting up data infrastructure
  • Developing, implementing and maintaining databases
  • Assessing quality of data and removing or cleaning data
  • Generating information and insights from data sets and identifying trends and patterns
  • Preparing reports for executive and project teams
  • Creating visualisations of data

What skills does a data analyst need to have?

A good data analyst has a blend of technical and soft skills.

  • Strong mathematical & numeracy skills.
  • Intermediate understanding of databases such as SQL Server, Oracle and SAP.
  • Understanding of reporting & data visualisation tools such as Business Objects, PowerBI and Tableau.
  • Understanding of website scripts such as XML, Javascript, JSON.
  • Understanding of ETL framework and ETL tools including Alteryx and Microsoft SSIS.
  • Digital marketing analytics tools including Google 360, Google Analytics, Google Tag Manager and Adobe Marketing Suite.
  • Excellent analytical skills - the ability to identify trends, patterns and insights from data.
  • Strong attention to detail.
  • Presentation skills – ability to write and speak clearly to easily communicate complex ideas in a way that is easy to understand.
  • Problem solving skills.
  • Communication skills with effective stakeholder management & conflict resolution skills.

What qualifications does a data analyst need?

Whilst a degree is not essential, data analysts often have tertiary qualifications or a background in statistics, maths, economics or data science. Candidates with strong academic results will be highly preferred as entry-level analysts than their counterparts.

What is the career path for a data analyst?

A data analyst can potentially progress into the following roles

Data analyst
Senior data analyst
Data scientist
Head of Data

 

Who does a data analyst report to?

A data analyst may report directly to the leader of a project or a department e.g. CMO, or they may report to a Chief Data Officer or Head of Analytics in a larger data analytics team.

How much does a data analyst earn?

Data analysts can earn between AUD65k for entry level roles up to AUD200k for more senior positions.

Sydney

 
Permanent (AUD/000)
-
Data Innovation
Data Analyst (Junior)
65 - 75
-
Data Analyst (Mid Weight)
75 - 85
-
Data Analyst (Senior)
85 - 100
-
Data Modeller (Junior)
70 - 80
-
Data Modeller (Mid Weight)
80 - 120
-
Data Modeller (Senior)
120 - 160
-
Data Researcher (Junior)
125 - 135
-
Data Researcher (Mid Weight)
135 - 145
-
Data Researcher (Senior)
145 - 155
-
Data Scientist (Junior)
100 - 120
-
Data Scientist (Mid Weight)
120 - 140
-
Data Scientist (Senior)
140 - 160
-
Senior Data Scientist (Junior)
160 - 170
-
Senior Data Scientist (Mid Weight)
170 - 180
-
Senior Data Scientist (Senior)
180 +
-
Chief Data Scientist (Junior)
180 - 190
-
Chief Data Scientist (Mid Weight)
190 - 220
-
Business Performance & Insights
Data Visualisation Specialist (Junior)
65 - 75
-
Data Visualisation Specialist (Mid Weight)
75 - 105
-
Data Visualisation Specialist (Senior)
105 - 130
-
Chief Data Scientist (Senior)
220 +
-

Melbourne

 
Permanent (AUD/000)
Contracting (AUD/hr)
Data Innovation
Data Scientist (Junior)
70 - 90
40 - 55
Data Scientist (Mid Weight)
90 - 120
55 - 75
Data Scientist (Senior)
125 - 200
75 - 150
Data Engineer (Junior)
80 - 110
50 - 70
Data Engineer (Mid Weight)
110 - 140
70 - 100
Data Engineer (Senior)
140 - 200
100 - 150
Data Modeller (Junior)
70 - 90
40 - 55
Data Modeller (Mid Weight)
90 - 120
55 - 75
Data Modeller (Senior)
125 - 160
75 - 120
Business Performance & Insights
Data Visualisation Specialist (Junior)
65 - 80
35 - 50
Data Visualisation Specialist (Mid Weight)
80 - 105
50 - 65
Data Visualisation Specialist (Senior)
105 - 140
65 - 90
Data Strategy Manager
120 - 160 +
n/a
Head of Data Analytics
160 - 250 +
n/a
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