ACT
Company Description
Showtime Consulting is a leading provider of Shielded Cloud and Digital Solutions across Australia and New Zealand. We specialise in delivering secure, enterprise-scale technology solutions across cloud, infrastructure, cybersecurity, DevSecOps, software engineering, data, AI/ML, and digital transformation programs.
We partner with government and enterprise organisations to build high-performing technology teams that deliver secure, scalable, and future-ready solutions within complex technology environments.
The Role
We are seeking an experienced GCP Data & MLOps Engineer to support the design, development, and delivery of modern data, AI/ML, and cloud-native solutions.
This role is suited to a hands-on engineer with strong experience across Google Cloud Platform, Dataflow, Apache Beam, BigQuery, Kubeflow, Python, and DevOps/MLOps practices. You will work across data pipeline development, AI solution delivery, model lifecycle management, cloud automation, and application development to support scalable and efficient platform outcomes.
Key Responsibilities
Design, build, and maintain data pipeline frameworks using Google Cloud Platform.
Develop customised data pipeline solutions using Dataflow and Apache Beam.
Build and maintain Dataflow Flex Template Frameworks and reusable Python libraries.
Develop scalable data processing and transformation solutions using Python and BigQuery.
Perform BigQuery data extraction, preprocessing, and automated job scheduling.
Design and implement Kubeflow Pipelines for automated ML pipeline creation and deployment.
Support AI/ML solution delivery across GCP-based platforms and services.
Implement DevOps and MLOps practices across the data and machine learning lifecycle.
Manage model lifecycle, maintenance, and governance using GCP Model Registry.
Enable continuous deployment of Django applications on Google Cloud Platform.
Automate deployment and management of Cloud Run services and Cloud Functions.
Implement CI/CD pipelines using Cloud Build and related GCP tooling.
Develop REST API-based microservices to support platform and application integration.
Implement security services including Secret Manager and Cloud KMS.
Build dashboards and web applications using Python Django and R Shiny.
Optimise application code, data pipelines, and technical deliverables to improve performance.
What You'll Need
Strong hands-on experience with Google Cloud Platform.
Experience developing data pipelines using Dataflow and Apache Beam.
Strong Python development skills and experience building reusable Python libraries.
Experience working with BigQuery for data extraction, preprocessing, and scheduling.
Experience building Dataflow Flex Template Frameworks is highly regarded.
Experience delivering AI-based solutions on GCP is advantageous.
Strong understanding of DevOps and MLOps practices.
Experience designing and implementing Kubeflow Pipelines is highly regarded.
Experience with GCP Model Registry and model lifecycle management is advantageous.
Experience developing REST APIs and microservices.
Experience with Python Django application development is highly regarded.
Experience deploying and managing Cloud Run and Cloud Functions.
Experience with automated CI/CD pipelines using Cloud Build.
Knowledge of Secret Manager, Cloud KMS, and cloud security practices is advantageous.
Experience with R Shiny dashboards is highly regarded.
Strong understanding of cloud-native application development and platform automation.
Strong analytical, troubleshooting, and performance optimisation skills.
Good communication skills with the ability to work across technical and business teams.
Why Join Us?
Work on modern GCP-based data, AI/ML, and platform engineering solutions.
Build scalable cloud-native data pipelines and machine learning workflows.
Gain exposure to Dataflow, Apache Beam, Kubeflow, BigQuery, and MLOps practices.
Contribute to automation, CI/CD, and cloud platform modernisation initiatives.
Collaborate with experienced cloud, data, software engineering, and delivery teams.
Join a consulting culture focused on innovation, technical excellence, and continuous improvement.
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