Python Developer

One of our clients is hiring for the role Python Developer / Data Engineer at Melbourne location

Role: Python Developer / Data Engineer

Location of work: Melbourne

Length of contract: 06 months

Contract extensions: Not Applicable

Security clearance: Permanent Resident with full working rights in Australia

Overview

This role combines core Python development with data engineering. The successful candidate will

prepare, process and transform raw data into structured, reliable outputs — building automated

pipelines and reporting solutions that make data accessible for analytics, reporting and operational

decision-making.

Key duties and responsibilities

Responsibilities include, but are not limited to, the following

• Develop and maintain Python applications for data manipulation and processing, applying language fundamentals (data structures, OOP, error handling) and libraries such as pandas and NumPy.
• Write and optimise SQL queries against relational databases, work with large datasets, and integrate Python applications with data sources via ORMs or direct connections.
• Build, schedule and maintain automation, workflow and ETL processes — including reporting pipelines run reliably using tools such as Apache Airflow or task schedulers.
• Produce structured reporting outputs such as Excel, PDF and dashboard-based reports from raw data (e.g., openpyxl, Plotly, Power BI integration).
• Apply sound software engineering practices — version control with Git, unit testing, and clear code documentation.
• Work effectively within an agile team and contribute to CI/CD pipelines.

Technical skills

• Core Python proficiency — strong grasp of language fundamentals (data structures, OOP, error handling) plus common libraries such as pandas and NumPy for data manipulation and processing.
• Database and SQL skills — ability to write and optimise queries against relational databases, work with large datasets, and integrate Python applications with data sources via ORMs or direct connections.
• Automation and scripting experience — building scheduled jobs, workflow automation and ETL processes; familiarity with tools such as Airflow or task schedulers to run reporting pipelines reliably.
• Reporting and output generation — experience producing structured outputs such as Excel, PDF or dashboard-based reports (e.g., openpyxl, Plotly, Power BI integration) from raw data.
• Software engineering practices — version control with Git, unit testing, code documentation, and comfort working in agile teams with CI/CD pipelines.

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