As a Data Platform Engineer within Engineering Data Hub, you will be at the forefront of designing and building a Platform to bolster the data and analytics capabilities. Your responsibilities will include configuring and setting up cloud infrastructure, deploying and operating data-oriented applications on Kubernetes, and working closely with other teams and platform users to gather requirements and maintain seamless operations. We are in an early development phase, which means you will have the unique opportunity of contributing directly to the Platform’s foundation. Your input will directly shape its trajectory, setting the stage for its future growth and success.
Responsibilities
- Public cloud infrastructure (Azure, AWS, or equivalent).
- Implementation of scalable infrastructure through an Infrastructure as Code (IaC) approach.
- CI/CD with tools such as GitHub Actions, ArgoCD, etc.
- Deployment and operation of applications and services on Kubernetes.
- Experience in deploying Kubernetes as well as automating application deployments to Kubernetes or equivalent solutions.
- Design and implementation of internal developer platforms.
Requirements
- Languages: Python, Go.
- Cloud infrastructure: Azure, Kubernetes.
- DevOps: Terraform, Crossplane, GitHub Actions, Flux, Helm, Prometheus, Grafana, Vault.
- PaaS: Databricks, Snowflake.
Desired Skills
- Networking, security, and reliability in enterprise cloud solutions.
- Tools and technologies for working with Big Data, including event streaming (e.g. Kafka, MQTT), large-scale data processing (e.g. Apache Spark, Ray), and storage solutions for Big Data (e.g. Apache Iceberg, Delta Lake).
- User and device authentication, data and resource access control, and data privacy protection.
