Company Description RANZ Tech helps organizations turn AI, data, and digital strategy into practical, measurable outcomes. The company brings together advisory, engineering, and delivery expertise to build secure, connected, and governed solutions that operate effectively in real-world environments. RANZ Tech supports clients across AI adoption, data platforms, cloud engineering, analytics, and digital transformation, with a solid focus on production-ready capabilities.

The team is dedicated to simplifying complexity, collaborating closely with clients, and maintaining a clear focus on delivery. The results RANZ Tech achieves for clients are the primary driver of its growth and reputation.

Role Description As a Data Engineer at RANZ Tech, you will design, build, and maintain scalable data pipelines and infrastructure that support analytics, AI, and digital solutions for client projects. You will work with cross-functional teams to understand data requirements, implement robust data models, and optimize Extract, Transform, Load (ETL) processes for performance, reliability, and security. Day-to-day responsibilities include developing data warehousing solutions, monitoring data quality, troubleshooting data issues, and contributing to continuous improvement of data engineering best practices.

You will also collaborate with data analysts and data scientists to ensure data is accessible, well-structured, and fit for production use. This is a full-time, hybrid role based in Melbourne,



VIC, with a mix of on-site client and team collaboration and some work-from-home flexibility.

Qualifications

- Strong Data Engineering skills, including building and maintaining scalable data pipelines and working with modern data platforms.
- Proficiency in Data Modeling to design efficient, reliable, and maintainable data structures for analytics and operational systems.
- Experience with Extract Transform Load (ETL) development, optimization, and orchestration using relevant tools and frameworks.
- Knowledge of Data Warehousing concepts and implementation, including star/snowflake schemas and performance tuning.
- Ability to perform Data Analytics, interpret results, and collaborate with stakeholders to translate data into actionable insights.
- Hands-on skills in SQL and at least one programming language commonly used in data engineering (e.g., Python, Scala, or Java).
- Familiarity with cloud data services (e.g., AWS, Azure, or GCP), distributed data processing frameworks, and modern data stack tools.
- Strong problem-solving abilities, attention to detail, and a collaborative approach to working with technical and non-technical teams.
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience.
- Experience working in consulting, professional services, or client-facing environments is beneficial.

📌 Data Engineer (Melbourne)
🏢 RANZ Tech
📍 Melbourne