DevOps Data Engineer

Company Background

Our client is a global technology company transforming the way brands and agencies make marketing decisions. Its platform enables marketers to plan and activate cross-channel, programmatic media campaigns using real-time research, proprietary audience data, advanced analytics, and more than 150 integrated partners including Facebook, Instagram, Pinterest, Snapchat, and Twitter. The company operates across North America, Europe, the Middle East, Asia, and Australia.

Project Description

We’re looking for a DevOps Engineer to build, operate, and scale the platforms behind data systems, run containerized workloads on Kubernetes and Linux-based environments, and help keep batch and streaming data pipelines reliable at scale.

Technologies

• Kubernetes
• Linux
• Spark
• Python
• AWS or other cloud platforms
• GitLab / GitHub
• CI/CD

What You'll Do

• Build, operate, and scale containerized data infrastructure on Kubernetes and/or Linux-based systems;
• Work with distributed data processing engines, such as Spark, across batch and streaming workloads;
• Develop automation scripts and internal tooling using Python;
• Improve reliability, observability, and performance of distributed systems;
• Support infrastructure operations, troubleshooting, and continuous improvement of platform stability;

Job Requirements

• 3+ years of commercial experience in DevOps, Infrastructure, or similar engineering roles;
• Solid Linux administration skills;
• Hands-on experience with containers and Kubernetes;
• Good understanding of distributed systems and data infrastructure concepts;
• Good Python scripting experience for automation and tooling;
• Hands-on experience with at least one cloud platform, preferably AWS;
• Experience with version control and CI/CD tools, such as GitLab or GitHub;
• Strong English communication skills, B1+ level or higher;
• Ability to work independently and collaborate effectively within a team;

Nice To Have

• Exposure to data warehouses, data lakes, or distributed data processing frameworks such as Hadoop, Spark, Flink, or Trino across batch and/or streaming workloads;
• Experience with GitOps tools, such as ArgoCD or Flux;
• Experience administering at least one NoSQL database, such as Redis, Elasticsearch, or MongoDB;
• Previous experience as a Data Engineer or Software Engineer with an infrastructure background;