Hands-on Databricks, supporting production ML products within an established data team right here in Brisbane! This contract role supports machine learning products already running in production. It’s a blend of BAU platform support, deployment governance, and technical enablement for Data Scientists working in Databricks. This is not a pure Data Scientist role, it’s ideal for someone who enjoys being the technical backbone of a data platform. What you will be working on: Supporting Databricks based ML products in production with in initial BAU focus Transitioning models from Databricks notebook prototypes into production utilising ML and pipeline best practices. Design, develop, deploy and maintain end to end machine learning and data pipelines Manage data and data pipeline operations including data migration, resource management, data pipeline configurations, and troubleshooting Collaborate with Data Scientists, Data Engineers, DevOps Engineers and Application developers to design, build, deploy, and maintain robust solutions to critical problems Write and review technical documents, including design, development, and collaborative code reviews. Monitor and enhance the performance, cost, stability, and operational efficiency of existing tools and services. Maintenance of the Databricks infrastructure (including UC catalogue, compute, users and updates). Experience: 3 years in a DevOps or platform role within AWS environments Understanding of cloud-native, Agile and DevOps operating models Experience coding, scripting in Python, Bash or PowerShell CI/CD pipeline automation using Azure DevOps Infrastructure as Code experience using Terraform Experience with cloud monitoring and logging - CloudWatch Strong Python and Spark experience, including Databricks Experience deploying and supporting ML models in production Solid understanding of the ML model lifecycle Experience with MLflow and Feature Stores Background in big data, scalable or shared system design Experience working with relational and non-relational data stores across varying data speeds Familiarity with unit testing, agile delivery, and change/incident management Ability to manage multiple priorities and projects effectively Qualifications: Degree in Computer Science, or similar, or equivalent practical experience IT or quantitative undergraduate degree AWS Cloud Certifications (Cloud Practitioner) Databricks certifications (Data Engineering Associate, Machine Learning Associate)
