We are seeking a Data Engineer with strong Python expertise to design and
maintain production-grade data pipelines, integrate diverse external data sources, and support machine learning workflows.
Role Overview
As a Data Engineer, you will be responsible for building scalable pipelines, orches trating workflows, and integrating structured and semi-structured data from multiple
sources. You will develop resilient ingestion frameworks, optimize SQL transforma tions, and apply best practices in testing and automation. While your focus will be on engineering, your work will directly enable advanced analytics and predictive modelling.
Key Responsibilities
Build ingestion workflows for APIs, web data, and files.
Handle structured and semi-structured formats (JSON, XML, HTML, CSV).
Apply resilient scraping practices, including session handling, proxies, and request automation.
Ensure compliance with security and access restrictions when integrating ex
ternal data sources.
Optimize SQL queries and transformations for analytics.
Design, build, and maintain robust Python-based data pipelines.
Implement testing frameworks and good engineering practices for reliability.
Ensure data quality, consistency, and scalability across workflows.
Required Skills & Experience
Expert-level Python for data engineering and workflow automation.
Knowledge of web scraping, ingestion workflows, and handling varied data
formats.
Experience designing and maintaining production-grade data pipelines.
Familiarity with best practices in testing, monitoring, and pipeline reliability.
Proficiency with version control (Git/GitHub/Azure DevOps).
Strong SQL skills for ETL and analytics.
Qualifications
BSc or MSc in Computer Science, Data Engineering, Software Engineering, or
related fields.
Equivalent practical experience will also be considered.
As an Australian-based company with English-speaking colleagues, fluency in
English is essential for success in our work. This is a full-time remote position.
If you are interested, kindly send your CV to