Join a leading automobile technology client's Data Analytics team as a DevOps/Platform Engineer to build and scale a self-service data platform using Terraform, AWS, and Kubernetes. Collaborate with technical leads and internal stakeholders to improve platform reliability, automation, and developer experience.
Key Highlights
Key Responsibilities
Technical Skills Required
Job Description
- Build and scale a self‑service data platform using Terraform, AWS, and Kubernetes
- High-impact backfill role with ownership of core cloud and platform automation
- Work in a collaborative Data Analytics team supporting global business units
We are hiring a DevOps / Platform Engineer to join on of leading innovative automobile technology client's Data Analytics team. The team plays a critical role in enabling analytical solutions across the company by building and operating a scalable, self‑service data platform.
You will work closely with two technical leads and collaborate with internal stakeholders across Global Operations, Finance, and product teams. There is no external customer interaction, allowing you to focus on platform reliability, automation, and developer experience.
What You’ll Do
- Manage and operate Kubernetes clusters and deploy new applications using Terraform
- Own Infrastructure‑as‑Code for AWS resources, with most of the stack managed through Terraform
- Provision and scale Kubernetes nodes as platform demand grows
- Build and integrate self‑service features tied to Terraform workflows
- Set up and maintain observability for infrastructure and applications
- Maintain multiple Terraform states across cloud and monolithic repositories
- Partner with horizontal teams to enable analytics capabilities for internal products
- Improve reliability following Kubernetes migration and reduce manual operational work
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- 3+ years of hands-on engineering experience
- Strong experience with Terraform (required) and managing large IaC codebases
- Solid expertise with AWS cloud services
- Experience administering Kubernetes and deploying containerized workloads
- Proficiency with Docker, Git, and CI/CD tools such as GitHub Workflows
- Experience with observability tools (Prometheus, StatsD, GCL)
- Strong Python skills
- Ability to work independently after a structured onboarding period
- Experience with data platforms such as Databricks, Snowflake, Fabric, or ClickHouse
- Experience managing multiple Terraform states and complex environments
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- Automates previously manual metric extraction processes
- Enables new capabilities and self‑service features on the data platform
- Improves platform reliability after Kubernetes migration
- Frees up team capacity by owning critical integration and automation work
- Part of the Data Analytics group supporting multiple business units
- Collaborative, platform‑focused culture with a strong emphasis on automation
- Hybrid work arrangement
- Visa sponsorship permitted
- Deliver assigned projects as a contributing team member
- Receive ongoing feedback from team leads
- Enable other engineers by completing platform integrations
- Operate independently after approximately two months of onboarding
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