Job Description

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- Build GCP data pipelines using Dataflow and Apache Beam
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- Deliver MLOps, Kubeflow and AI/ML platform solutions
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- Develop Python, Django, REST APIs and CI/CD automation
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- Build GCP data pipelines using Dataflow and Apache Beam
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- Deliver MLOps, Kubeflow and AI/ML platform solutions
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- Develop Python, Django, REST APIs and CI/CD automation
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Company Description

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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.

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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.

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The Role

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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.

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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.

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Key Responsibilities

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- Design, build, and maintain data pipeline frameworks using Google Cloud Platform.
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- Develop customised data pipeline solutions using Dataflow and Apache Beam.
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- Build and maintain Dataflow Flex Template Frameworks and reusable Python libraries.
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- Develop scalable data processing and transformation solutions using Python and BigQuery.
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- Perform BigQuery data extraction, preprocessing, and automated job scheduling.
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- Design and implement Kubeflow Pipelines for automated ML pipeline creation and deployment.
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- Support AI/ML solution delivery across GCP-based platforms and services.
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- Implement DevOps and MLOps practices across the data and machine learning lifecycle.
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- Manage model lifecycle, maintenance, and governance using GCP Model Registry.
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- Enable continuous deployment of Django applications on Google Cloud Platform.
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- Automate deployment and management of Cloud Run services and Cloud Functions.
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- Implement CI/CD pipelines using Cloud Build and related GCP tooling.
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- Develop REST API-based microservices to support platform and application integration.
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- Implement security services including Secret Manager and Cloud KMS.
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- Build dashboards and web applications using Python Django and R Shiny.
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- Optimise application code, data pipelines, and technical deliverables to improve performance.
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What You'll Need

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- Strong hands-on experience with Google Cloud Platform.
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- Experience developing data pipelines using Dataflow and Apache Beam.
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- Strong Python development skills and experience building reusable Python libraries.
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- Experience working with BigQuery for data extraction, preprocessing, and scheduling.
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- Experience building Dataflow Flex Template Frameworks is highly regarded.
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- Experience delivering AI-based solutions on GCP is advantageous.
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- Strong understanding of DevOps and MLOps practices.
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- Experience designing and implementing Kubeflow Pipelines is highly regarded.
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- Experience with GCP Model Registry and model lifecycle management is advantageous.
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- Experience developing REST APIs and microservices.
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- Experience with Python Django application development is highly regarded.
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- Experience deploying and managing Cloud Run and Cloud Functions.
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- Experience with automated CI/CD pipelines using Cloud Build.
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- Knowledge of Secret Manager, Cloud KMS, and cloud security practices is advantageous.
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- Experience with R Shiny dashboards is highly regarded.
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- Strong understanding of cloud-native application development and platform automation.
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- Strong analytical, troubleshooting, and performance optimisation skills.
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- Valuable communication skills with the ability to work across technical and business teams.
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Why Join Us?

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- Work on modern GCP-based data, AI/ML, and platform engineering solutions.
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- Build scalable cloud-native data pipelines and machine learning workflows.
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- Gain exposure to Dataflow, Apache Beam, Kubeflow, BigQuery, and MLOps practices.
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- Contribute to automation, CI/CD, and cloud platform modernisation initiatives.
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- Collaborate with experienced cloud, data, software engineering, and delivery teams.
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- Join a consulting culture focused on innovation, technical excellence, and continuous improvement.
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📌 GCP Data Engineer (New South Wales)
🏢 Showtime Consulting
📍 New South Wales