Senior DevOps Engineer (all genders) | Data Platform

Overview

In this role you own and optimize our self-hosted data stack, including Kafka, Debezium, and Kubernetes, to power reliable data pipelines for our international marketplace. You will partner with the Data & Analytics leadership to drive cross-quarter initiatives and design decisions, shaping scalable, cost-conscious data infrastructure. You’ll work in a flat, startup-minded team and contribute to a secure, automated, and observable platform. This is a hands-on position with broad influence on data architectures and on-call incident response.

Leistungen / Benefits

• Remote option within Germany or office locations: Cologne, Darmstadt, Düsseldorf, Berlin
• Relocation package
• Urban Sports Club and gym benefits
• 30 days vacation per year and sabbatical opportunity
• Deutschlandticket subsidy
• Language learning programs and training opportunities

Verantwortungsbereiche

• Operate and own the Kafka backbone, including ACLs, quotas, certificates, upgrades, and disaster recovery
• Manage Debezium-based CDC pipelines, connectors, snapshots, offsets, and sink loaders
• Run workloads on Kubernetes with Navarch, covering resource management, autoscaling, and debugging
• Automate access management and infrastructure as code across GitLab CI/CD pipelines
• Oversee observability and cost management with Datadog, and monitor Kafka retention and log volumes
• Participate in triage on a rotating schedule, supporting ingestion, schema alerts, and analyst requests
• Act as a senior sparring partner to drive design reviews and multi-quarter initiatives
• Potential to grow into BigQuery architecture (access frameworks, partitioning, pipelines)
• Optional: participate in 24/7 on-call rotation

Zentrale Anforderungen

• Several years of production infrastructure experience with on-call rotations
• Deep hands-on Kafka broker operations (sizing, partitioning, replication, ISR, upgrades)
• Experience with cross-system data replication (Debezium on Kafka Connect or similar)
• Strong Kubernetes production experience with resource management and autoscaling
• Infrastructure as code across environments (Terraform and Ansible; Pulumi, Helm appreciated)
• Least-privilege IAM across multiple environments, ideally with GCP (or AWS/Azure knowledge)
• Production-grade Python and SQL with cost-conscious data practices
• Comfort in a low-process, Kanban environment with self-organizing senior engineers
• Fluent in English (C1) and able to work in international teams
• Optional: interest in data modeling/dbt, orchestration (Airflow, Dagster), or stream processing (Beam, Flink, Spark)

• Strong problem-solving and debugging reflexes
• Collaborative, self-organizing attitude
• Willingness to automate recurring tasks and reduce manual work
• Apache Kafka
• Kafka Connect / Debezium
• Kubernetes