Top AWS Jobs in Sydney

Design and build scalable cloud data infrastructure, pipelines, and reusable data products. Ingest and transform data, enable self-serve analytics, deliver visualisations, contribute to governance and platform strategy, and mentor teammates while collaborating cross-functionally.

Develop and maintain scalable backend services and APIs, collaborate with frontend developers, and lead new features and infrastructure improvements.

Lead and deliver instructor-led (onsite and virtual) technical training and lab-based workshops for cybersecurity practitioners. Build and maintain advanced training content, learning paths, and certification programs for OpenCTI/OpenAEV. Partner cross-functionally to shape program architecture, surface product feedback, mentor junior staff, and document scalable delivery standards.

Design and execute automated tests for APIs, web, and enterprise applications. Collaborate with developers on requirements, participate in release planning, build/maintain test suites, diagnose bugs, and validate system quality prior to release. Contribute to test strategy, review design documents, and improve data product QA processes.

The Senior Technical Consultant will implement and integrate Blue Yonder WMS solutions, develop technical concepts, ensure system integration, and enhance platform functionality based on customer feedback.

Operate and maintain cloud platform infrastructure and Kubernetes clusters, perform software releases and infrastructure updates, manage Linux/Windows servers and databases, support onboarding/migrations, test backups and DR plans, perform daily monitoring and maintenance, create documentation, and participate in an on-call rotation.

Lead research and provide actionable, high-impact insights on Microsoft licensing and software contracting. Advise clients on negotiation strategies, publish thought leadership, support sales and events, and drive research process improvements while collaborating across global teams.

The Senior Machine Learning Engineer will design, train, and deploy ML models for optimizing revenue in advertising, taking ownership of product development and leading the ML discipline.

Build and secure Overflow's cloud platform: manage containerized AWS infrastructure (ECS Fargate), automate CI/CD with GitHub Actions, embed automated security testing, implement observability, and support SOC 2 and PCI-DSS compliance.

The Senior Data Engineer will engineer and improve enterprise-scale data platforms on AWS, design and build end-to-end data pipelines, and optimize data processing solutions using Apache Spark and Python. Responsibilities include data governance, compliance controls, and collaboration with cross-functional teams to support analytics and data integration needs.

Develop and optimize backend architecture for a multi-brain AI trading system. Design and implement AI/ML models and workflows, integrate blockchain and smart contracts, build and maintain APIs, databases, and cloud infrastructure, perform code review, testing, debugging and performance optimization, and ensure security, data integrity, and production readiness.

Act as Tier 2 escalation for complex software issues across microservices, APIs, containers, and integrations. Troubleshoot deployments and OS issues, build and optimize automations (Superblocks, n8n, Tines, webhooks, Zendesk), analyze ticket trends, document runbooks, and collaborate with Engineering to surface and resolve product bugs.

Design and execute end-to-end data migration and modernisation to AWS. Build scalable ETL/ELT pipelines (Glue, PySpark, Lambda), migrate databases with AWS DMS/SCT, load and optimise cloud data warehouses (Redshift), ensure data quality, governance, security (IAM, encryption), and monitor/troubleshoot migration workflows while collaborating with stakeholders for cutover planning.

Lead design and delivery of Generative AI solutions using Amazon Bedrock and orchestration frameworks. Build CI/CD pipelines, manage full-stack AWS infrastructure, ensure observability and AI governance, collaborate with stakeholders, apply Agile practices, mentor engineers, and integrate new AI innovations into production systems.