Job Description

Build GCP data pipelines, AI/ML solutions and MLOps frameworks using Dataflow, Apache Beam, BigQuery, Kubeflow and Python.

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13th August, 2026

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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.
n 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 platform solutions.
n This role is suited to a hands-on engineer with solid experience across Google Cloud Platform, Dataflow, Apache Beam, BigQuery, Kubeflow, Python, Django, and DevOps/MLOps practices. You will work across data pipeline development, AI solution delivery, model lifecycle management, cloud automation, dashboard deployment, and application development to support scalable and efficient platform outcomes.

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Key Responsibilities

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- Design, build, and maintain customised data pipeline frameworks using Google Cloud Platform.
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- Develop scalable data processing solutions using Dataflow, Apache Beam, Python, and BigQuery.
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- Build and maintain Dataflow Flex Template Frameworks and domain-specific Python libraries.
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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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- Deliver AI-based solutions on the GCP platform.
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- Apply DevOps and MLOps practices across the data and machine learning lifecycle.
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- Implement automation and monitoring across data flows, ML systems, and cloud services.
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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 GCP.
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- Automate deployment and management of Cloud Run services and Cloud Functions.
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- Implement automated CI/CD pipelines using Cloud Build.
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- Develop REST API-based microservices to support platform and application integration.
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- Implement Secret Manager and Cloud KMS, including deterministic encryption.
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- Develop customised web applications for AI Platform resource creation and management.
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- Deploy and maintain dashboards using R Shiny and Python Django.
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- Optimise application code, data pipelines, and technical deliverables to improve performance and efficiency.
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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 customised data pipelines using Dataflow and Apache Beam.
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- Strong Python development skills, including experience building reusable Python libraries.
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- Experience working with BigQuery for data extraction, preprocessing, and automated 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 applying DevOps methodologies to machine learning systems.
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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 microservices using REST APIs.
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- Experience with Python Django application development is highly regarded.
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- Experience automating Cloud Run and Cloud Functions deployments.
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- Experience with automated Cloud Build implementations.
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- Knowledge of Secret Manager, Cloud KMS, and deterministic encryption is advantageous.
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- Experience deploying dashboards using R Shiny or Python Django is highly regarded.
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- Experience developing customised web applications for AI platform resource management is advantageous.
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- Strong understanding of cloud-native application development and platform automation.
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- Strong analytical, troubleshooting, optimisation, and problem-solving skills.
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- Good 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, dashboarding, 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 & AI/MLOps Engineer (New South Wales)
🏢 Showtime Consulting
📍 New South Wales