We are looking for an engineer who can combine data engineering, platform thinking, and DevOps practices to improve how data is produced, managed, and consumed across Arrive.

In this role, you will build platform capabilities that make data more reliable, discoverable, and self-serve for internal teams. You'll work on the infrastructure, tooling, and operational practices that help data users move faster with confidence. You will help us drive further a global multi-region platform that supports 700 annual users on Snowflake, across 100+ teams.

What You'll Do :

- Design and manage Snowflake infrastructure using Terraform, including access control, resources management, features addition and cost optimization

- Improve the developer experience for data teams through self-service tooling and documentation-as-code

- Enable teams to onboard datasets, build pipelines, and access trusted data with minimal manual

support

- Apply DevOps practices to data platforms, including CI/CD for dbt projects, infrastructure-as-code, automated testing, and reproducible environments

- Design, deploy, and optimize Airflow infrastructure to support reliable data workflows at scale

- Measure platform adoption, gather feedback from internal users, and continuously reduce friction

- Explore and apply AI-assisted workflows to improve data platform operations, developer productivity, documentation, and support for internal data users

You will Thrive in This Role If You :

- Have 6+ years of experience in data engineering, platform engineering, or DevOps, with a strong focus on reliable, scalable data platforms

- Have practical experience with tools and practices such as Terraform, dbt, Snowflake, and CI/CD, and care deeply about reproducibility, reliability, and team enablement

Nice to Have :

- Experience running platform services on Kubernetes

- Experience using Helm to manage deployments

- Experience building internal developer platforms or self-service tooling