Senior Software Engineer, Data Engineering

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Global Technology Solutions (GTS) at ResMed is a division dedicated to creating innovative, scalable, and secure platforms and services for patients, providers, and people across ResMed. The primary goal of GTS is to accelerate well-being and growth by transforming the core, enabling patient, people, and partner outcomes, and building future-ready operations. The strategy of GTS focuses on aligning goals and promoting collaboration across all organizational areas. This includes fostering shared ownership, developing flexible platforms that can easily scale to meet global demands, and implementing global standards for key processes to ensure efficiency and consistency. At ResMed, we don't just build technology - we create solutions that transform lives. As a global leader in connected devices and digital health, we empower millions of people worldwide to sleep, breathe, and live better lives. We are seeking a Senior Software Engineer to join our Global Data Platform Engineering team and help build the next generation of ResMed's enterprise data ecosystem. This is a senior individual contributor role for an engineer who combines strong software engineering fundamentals with deep expertise in platform engineering, cloud-native development, and modern data platforms. In this role, you will design, build, and operate scalable self-service platform capabilities that power analytics, data products, AI/ML workloads, and engineering productivity across the organization. If you enjoy solving complex engineering challenges end-to-end, building production-grade systems, and working across frontend, backend, cloud infrastructure, and data services, this role offers the opportunity to make meaningful global impact at scale. Let's talk about Responsibilities As a Senior Software Engineer, you will contribute to the architecture, development, and operational excellence of ResMed's Global Data Platform. You will: Design, build, and maintain scalable self-service data platform capabilities supporting ingestion, orchestration, transformation, and data delivery workflows. Develop modern frontend applications and platform experiences using React and TypeScript. Build backend platform services and APIs using Python and cloud-native architectures. Develop reusable frameworks, SDKs, APIs, and platform tooling that improve developer productivity and enable self-service capabilities. Lead the evolution of the platform toward a cloud-native, Kubernetes-first architecture on AWS. Build cloud-native streaming services and event pipelines leveraging Kafka. Provision and manage infrastructure using Terraform and Infrastructure-as-Code best practices. Implement CI/CD automation, deployment pipelines, observability, and operational best practices. Ensure platform reliability, scalability, security, and performance across production environments. Collaborate closely with product managers, data engineers, analytics engineers, ML engineers, and application teams to deliver high-impact platform capabilities. Facilitate technical design discussions and mentor engineers across frontend, backend, and platform engineering best practices. Contribute to shared standards, reusable patterns, and engineering excellence across the broader platform organization. Let's talk about Qualifications and Experience Required: Bachelor's or Master's degree in Computer Science, Software Engineering, or related technical field, or equivalent practical experience. 8+ years of professional software or platform engineering experience building production-grade applications, platform services, or distributed systems. Strong frontend development experience using: React, TypeScript/JavaScript, Modern frontend architecture and component design patterns. Strong backend development experience using Python and API-driven service development. Hands-on experience with AWS cloud services. Deep hands-on experience with enterprise-scale relational and NoSQL databases, including Snowflake, DynamoDB, PostgreSQL, MySQL, SQL Server, and MongoDB, with strong understanding of performance, scalability, and data modeling principles. Strong experience with Kubernetes, Docker, and containerized application development. Experience provisioning and managing cloud infrastructure using Terraform and Infrastructure-as-Code principles. Strong understanding of distributed systems, microservices architecture, and event-driven design patterns. Experience implementing CI/CD pipelines using tools such as GitHub Actions, or similar platforms. Experience implementing observability and monitoring using tools such as Datadog, Grafana, Prometheus, OpenTelemetry, or CloudWatch. Strong collaboration and communication skills with experience working across cross-functional engineering organizations. Preferred: Experience building or operating enterprise-scale data platforms. Experience with orchestration frameworks such as Airflow or Dagster. Familiarity with streaming and event

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