infrastructure
Posted Jan 22Senior Data Platform Engineer
at ResMed
San Diego United States, United StatesOn-site
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Responsibilities
- Develop high-quality analytics and data models in Snowflake using dbt or similar frameworks, with a focus on performance, correctness, and maintainability.
- Implement automation, monitoring, and observability to ensure reliable and resilient data pipelines in production.
- Collaborate closely with product managers, analytics engineers, data scientists, and application engineers to deliver data products that drive business and clinical outcomes.
- Support advanced analytics and ML use cases by building feature pipelines and data foundations for classical ML models and emerging AI-driven workloads.
Requirements
- This is a senior individual contributor role for an engineer who combines strong software engineering fundamentals with deep data engineering and analytics experience.
- You will design, build, and operate reliable, scalable data systems that power analytics, data products, and advanced AI/ML use cases across the organization.
- You will: Design, build, and maintain scalable data pipelines for ingestion, transformation, and delivery using Python, SQL, Spark, APIs, and modern cloud-native tools.
- What You Bring (Must-Have) Bachelor’s degree in a STEM field or equivalent practical experience.
- experience as a data engineer or senior software engineer working on data-intensive systems (typically 5–8+ years). Strong SQL expertise and
- experience with data modeling on large-scale analytical platforms (Snowflake preferred). Proven
- experience building and operating production data pipelines using Python and cloud services.
- Proficiency with dbt or similar transformation and analytics engineering tools.
- Solid software engineering fundamentals, including system design, debugging, performance optimization, and maintainable code practices.
- Experience with Git/GitHub workflows, including pull requests, code reviews, and collaborative development. Hands-on
- experience building or working with CI/CD pipelines (GitHub Actions preferred), including automated testing and deployments.
- Ability to work effectively across both data engineering and analytics engineering responsibilities. Strong hands-on
- experience building and operating data systems on AWS, including designing cloud-native architectures and working with services such as S3, IAM, EC2/ECS/EKS, Lambda, Glue, EMR, or related AWS data and compute services. Nice-to-Have