Data & Analytics Recruitment Australia

These roles are often confused but serve very different purposes. A data analyst interprets existing data to answer business questions — think dashboards, reporting, and trend analysis. A data scientist builds predictive models and applies statistical methods to generate forward-looking insights. A data engineer builds and maintains the infrastructure that makes all of this possible — pipelines, warehouses, and data lakes. Most organisations need all three, but the right starting point depends on your data maturity. We help you figure out what to hire first.

Data Analysts typically earn $80,000 to $120,000 depending on seniority and tooling expertise. Data Scientists range from $110,000 to $170,000, with machine learning specialists commanding a premium. Data Engineers are among the most in-demand roles in the market, typically earning $120,000 to $180,000. Analytics Managers and Heads of Data sit between $160,000 and $230,000. Contract day rates for senior data engineers and ML engineers average $900 to $1,300 per day.

We assess candidates across the full modern data stack: SQL and Python as baseline requirements; cloud platforms including AWS (Redshift, Glue, Athena), Azure (Synapse, Data Factory), and GCP (BigQuery, Dataflow); visualisation tools including Power BI, Tableau, and Looker; and orchestration tools including Airflow and dbt. For data science roles, we assess proficiency in scikit-learn, TensorFlow, PyTorch, and MLflow. We tailor the technical assessment to your specific stack.

The best data professionals are rarely on job boards. Our consultants maintain active relationships with senior data engineers, scientists, and analytics leaders through industry communities, conference networks, and direct outreach. We invest in these relationships continuously, not just when a role opens. This means when you need someone exceptional, we can often make a call rather than post an ad.

Yes. We recruit across permanent, fixed-term, and contract engagements. Many organisations use permanent staff for core data platform ownership and contractors for specific project delivery — a data migration, a new ML model build, or a BI platform uplift. We can advise on the right mix and manage both streams simultaneously.