Data Engineer - Cloud Infrastructure

Apple delivers the most popular cameras in the world. Each product release provides breakthroughs in photography with stunning camera features that customers love. Our cameras deploy imaging complexity at the frontier of traditional camera engineering methods. Data volumes are growing to meet this need across camera simulations, performance calibrations, measurement results, and their correlations. Our team's task is to build a comprehensive aggregate data layer that enables efficient and flexible executive reporting, highly customized data applications, and powerful ML inference and analysis.

We are seeking a highly motivated software engineer to manage the deployment of scalable cloud-native services, build observability tools, implement infrastructure as code automation, and create AI agents in a modern data layer.

Description

In this role, you will collaborate with a team of engineers to lead the design and development of observability solutions for Camera Data Engineering products and infrastructure.","responsibilities":"As a Data Engineer, you will use open source and internal tools to automate and manage the deployment of our application stack across public and on-prem cloud providers, implement best practices for application observability and alerting, and build powerful data integrity tooling to detect and correct issues in our data pipelines. You will be responsible for providing technical guidance, sharing observability know-how, leveraging AI pipelines, and mentoring the team to develop and deliver best-of-class solutions.

Preferred Qualifications

Experience with large-scale observability visualization systems with knowledge of popular visualization tools like Grafana, Data Dog, and ELK stack

Ability to build CI pipelines and automation tools using tools such as Jenkins, GitHub Actions, CircleCI, etc.

Experience with Infrastructure-as-Code (IaC) tools such as Terraform, OpenTofu, or Pulumi

Working knowledge with Kubernetes networking

Experience with Snowflake including monitoring techniques

Minimum Qualifications

BS or higher in Computer Science in Data Engineering, Data Science, or related fields.

Experience managing cloud-native applications leveraging AWS including EKS, Kubernetes and S3

Observability and telemetry tools such as CloudWatch, Splunk, Prometheus, OpenTelemetry

Experience with tools such as Helm, Flux, ArgoCD