DevOps Engineer

We are looking for a DevOps engineer ,with strong coding abilities, to build and maintain the foundational backend services, tooling, and automation for Rise’s Ad Serving Platforms.

In this dynamic and collaborative environment, you will be an integral part of a team managing a large volume of data, operating at a significant scale, and handling substantial traffic. You will be responsible for cloud infrastructure, creating CI/CD flows, Production and dev environments, and more.

Requirements:

Minimum of 2 years as a DevOps Engineer.
At least 1 year of production experience with Kubernetes.
Proficiency in a programming language such as Golang or Python.
Experience with monitoring tools like CloudWatch, Datadog, Grafana.
Hands-on experience with cloud infrastructure platforms such as AWS, GCP, etc.
Proficient in using IaC tools like Terraform, Pulumi, CloudFormation, etc.
Strong knowledge of CI/CD systems such as GitHub Actions, Jenkins, CircleCI, etc.
Hands-on experience with Linux operating systems, Bash scripting, and computer networking.
Ability to clearly communicate in both technical and non-technical settings.

Responsibilities:

Design and build efficient, high-quality cloud architectures to meet organizational needs.
Manage, monitor, and scale our distributed, highly available SaaS platform to ensure reliability and performance.
Work closely with engineering teams to ensure their applications are scalable and performant.
Develop innovative solutions to complex problems, implementing them independently or in collaboration with other teams.
Debug production issues across all tiers of a massive distributed system, spanning dozens of services.
Continuously work to enhance our core platform architecture.
Embed with various teams to promote best practices related to reliability, scalability, and observability.
Actively pursue knowledge and skills in engineering best practices to stay current in the field.

Adventeges:

Advanced knowledge and experience with Pulumi.
Experience in building and managing data pipelines.
Proficiency in using Apache Airflow for workflow automation.
Hands-on experience with AWS EMR and Apache Spark for big data processing.
Knowledge of Google BigQuery for data warehousing and analytics.