Data Scientist
Role details
Job location
Tech stack
Job description
RPMGlobal (RPM) is seeking a highly skilled and experienced Data Scientist to join our team working on advanced analytics and data-driven products within a modern Azure-based platform., This is a permanent full-time role based in our Brisbane CBD headquarters. This position is in-office; however, it allows for ad hoc working from home.
This role is ideal for someone who enjoys working across both data science and data engineering disciplines - designing scalable data pipelines, optimising SQL-based systems, and building intelligent solutions leveraging large language models., * Design, develop, and optimise ETL pipelines using Microsoft SQL Server
- Implement and maintain incremental data processing using Change Tracking / CDC
- Build and maintain CI/CD pipelines using Azure DevOps
- Develop and deploy data science solutions, including LLM-based features
- Work with Azure cloud services to build scalable, production-grade solutions
- Collaborate with product and engineering teams to deliver data-driven features
- Troubleshoot and performance tune complex SQL workloads
Requirements
- Bachelor's degree in Data Science, Computer Science, or a related field
- Strong expertise in Microsoft SQL Server, including:
- ETL development
- Query performance tuning
- Change Data Capture (CDC) and Change Tracking
- Experience with Azure DevOps, including CI/CD pipeline implementation
- Hands-on experience with large language models and tools such as Semantic Kernel
- Strong experience working with the Azure cloud platform
- Proven track record in developing commercial engineering or technical applications
- Strong communication skills and a collaborative mindset
- Strong command of the English language in both verbal and written form
- Must have the legal right to work in Australia
Highly Regarded Experience
- Experience in data engineering or building data platforms
- Experience with Databricks, Azure OneLake, or similar lakehouse technologies
- Exposure to distributed data processing frameworks (e.g. Spark)
- Experience in the mining or resources industry