Senior Cloud Engineer developing and managing cloud infrastructure for CHEP’s global operations. Collaborating with teams to optimize CI/CD pipelines and enhance developer experience.
Responsibilities
Design, orchestrate, and maintain scalable cloud infrastructure, working with engineers to automate processes and improve efficiency.
Collaborate with Innovation Squads, Product Success, and other teams to maintain fast, reliable, and resilient CI/CD pipelines, empowering engineers to self-service their infrastructure needs.
Support the development, testing, and maintenance of disaster recovery scenarios to ensure system availability and business continuity.
Develop and deploy automated tools that enhance the developer experience, simplifying infrastructure management and deployment processes.
Monitor performance, capacity, and availability of systems and infrastructure, working cross-functionally to troubleshoot and resolve platform-related issues.
Create and maintain technical documentation, ensuring it is fit for use in design reviews, incident response, and support processes.
Ensure best practices in cloud security, governance, and compliance are implemented across all cloud platform services.
Stay up-to-date on emerging cloud technologies and trends, applying knowledge to continuously improve the scalability and performance of cloud platforms.
Requirements
BS degree in Data Science, Computer Science, Engineering, Math, Statistics, Physics, or similar formal training or equivalent
Proven experience with looking after data science environments
Proven experience with looking after data storage systems with high availability and database tuning
Proven experience with FinOps and being able to optimize spend for CE impact
Experience with working with IoT and Edge interaction with the Cloud
5 years relevant experience in Cloud Engineering or adjacent fields
Installed, operated, and managed several data science and machine learning frameworks, or developed own data science methodologies
Experience with Continuous Integration and Continuous Deployment
Experience operating, optimizing, querying, and administering databases (such as Iceberg, Postgres, Patroni, DuckDB, TimescaleDB, etc.)
Comfortable using and working in a polyglot computer language environment (Python, Go, Julia etc.)
Experience with Amazon Web Services (S3, EKS, ECR, EMR, etc.)
Experience with containers and orchestration (e.g. Docker, Kubernetes)
Experience with Big Data processing technologies (Kubeflow, Spark, Hadoop, Flink etc)
Experience with interactive notebooks (e.g. JupyterHub, Databricks)
Experience with Git Ops style automation
Experience with *ix (e.g, Linux, BSD, etc.) tooling and scripting
Participated in projects that are based on data science methodologies, and/or physical experiments, or statistical analysis – especially in a data engineer and dev ops capacity.
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