dnata Airport Services Australia are excited to announce a new opportunity for a Data Analyst to join our dynamic Projects Team. In this role, you will report directly to the Manager – Strategic Projects. 

The Data Analyst is responsible for supporting operational performance by turning complex data into actionable insights. This role will focus on analysing workforce, operational, and financial data to improve reporting, support business decisions, and enable operational efficiency. 

Key Responsibilities: 

• Gather, clean, and analyse large datasets related to operations, workforce, and performance. 

• Develop dashboards and reports to monitor key performance indicators (KPIs) such as turnaround times, SLA adherence, and productivity metrics. 

• Provide insights to identify trends, inefficiencies, and opportunities for improvement. 

• Automate and streamline reporting processes to reduce manual effort and increase data accuracy 

• Create and maintain interactive dashboards using Power BI, Tableau, or similar tools. 

• Translate complex data into clear, actionable visualizations and reports for stakeholders. 

• Conduct trend analysis and provide data models to support business forecasting and planning.  

• Ensure data quality, consistency, and integrity across systems and reports. 

• Perform root cause analysis on operational issues using data insights. 

• Collaborate with internal teams to improve data structure, reporting accuracy, and availability. 

Preferred Skills & Tools: 

• Proven experience as a Data Analyst, ideally in aviation, logistics, or operational environments. 

• Proficient in SQL, Excel, and BI tools such as Power BI or Tableau. 

• Strong analytical skills, with experience in statistical analysis and reporting. 

• Ability to work with large, complex datasets and relational databases. 

• Excellent communication skills and ability to present data-driven insights clearly. 

• Experience with workforce or operational planning data is a plus. 

• Knowledge of Python, R, or other statistical programming languages. 

• Experience in predictive analytics and/or machine learning techniques. 

• Understanding of on-time performance, turnaround metrics, or service level tracking in operational contexts.