DevOps Engineer III

ZoomInfo’s Infrastructure Engineering organization is looking for a results-oriented DevOps Engineer III to strengthen our data platform teams. You will help build and maintain cloud-native data streaming, processing, and analytics infrastructure in AWS and GCP, working closely with Senior and Staff DevOps Engineers to deliver reliable, scalable systems that power our industry-leading GTM intelligence products.

What You'll do:

• Contribute to the design, provisioning, and management of data services on Kubernetes-based platforms (Amazon EKS & Google Kubernetes Engine).


• Implement infrastructure as code with Terraform, ensuring security, scalability, and cost awareness.


• Develop and maintain CI/CD pipelines (Jenakins, Argo CD, GitHub Actions) to enable automated testing and deployments.


• Deploy and support cloud-native data services such as Amazon Kinesis, AWS Glue, Google Pub/Sub, Dataflow, and BigQuery.


• Leverage AI-powered tooling (e.g., GitHub Copilot, generative-AI chat/ops assistants, and AIOps platforms) to accelerate script generation, configuration validation, and incident troubleshooting.


• Create automation scripts and internal tooling in Python to streamline DevOps workflows.


• Assist in establishing monitoring, logging, and alerting using Prometheus, Grafana, CloudWatch, or Datadog; incorporate AI-driven anomaly detection where applicable.


• Participate in on-call rotations, incident triage, and post-incident reviews; apply SRE best practice.


• Collaborate with engineers and software developers to ensure infrastructure aligns with application requirements and company standards.


• Document infrastructure, runbooks, and lessons learned to promote knowledge sharing across teams.

What you bring:

• 4–6 years in a DevOps, Site Reliability Engineering, or Cloud Infrastructure role.


• Production experience with AWS and/or GCP data services (e.g., Kinesis, Pub/Sub, Dataflow, BigQuery).


• Hands-on experience managing containerized workloads on Kubernetes (EKS, GKE, or self-managed clusters).


• Solid understanding of Terraform (or similar IaC tools) and Git-based workflows.


• Working knowledge of CI/CD platforms such as Jenkins, Argo CD, and/or GitHub Actions.


• Proficiency with Python or another scripting language for automation.


• Familiarity with observability stacks (CloudWatch, Datadog, etc.).


• Fundamental grasp of SRE principles—service reliability, incident response, and performance monitoring.


• Effective communication skills and a collaborative mindset.

Preferred Qualifications

• Demonstrated experience using AI-powered copilots, chat assistants, or AIOps platforms to accelerate infrastructure work or incident resolution.


• Experience with workflow orchestration tools (Apache Airflow, Cloud Composer).


• Exposure to big-data frameworks (Spark, Flink) or modern data-lake architectures.


• Knowledge of cost-optimization techniques for cloud resources.


• Familiarity with event-driven architectures and message queues (Kafka, RabbitMQ).


• Understanding of GitOps workflows and service mesh technologies such as Istio.

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