K

Senior Data Infrastructure Engineer - Kafka, Kubernetes, and Data Pipelines

Germany
Visa Sponsorship Relocation
This Job is No Longer Active This position is no longer accepting applications

Own and operate Kaufland’s self-hosted Apache Kafka backbone, Debezium CDC pipelines, and Kubernetes-based data infrastructure. Drive automation, observability, and cost management while supporting triage and senior-level design reviews. Lead multi-quarter initiatives with a focus on scalability and reliability.

Key Highlights
End-to-end ownership of Apache Kafka, Schema Registry, and Debezium-based CDC pipelines
Hands-on Kubernetes operations for Navarch workflow orchestrator (~7,500 tasks/day)
Automate infrastructure, access management, and observability with a cost-conscious mindset
Key Responsibilities
Run and own self-hosted Apache Kafka backbone and Schema Registry, including ACLs, client quotas, certificates, upgrades, and disaster recovery
Operate Debezium-based change data capture pipelines, managing connectors, snapshots, offsets, replica lag, and BigQuery sink loaders
Run workloads on Kubernetes, including Navarch workflow orchestrator, owning resource management, autoscaling, and debugging
Automate access management and infrastructure as code across self-hosted GitLab CI/CD pipelines
Own observability and infrastructure costs using Datadog, Slack-native alerting, and cost tracking for K8s, Kafka retention, and log volumes
Carry triage duties one week in three, handling ingestion requests, access requests, schema alerts, and supporting analysts
Act as a senior sparring partner, driving design reviews and multi-quarter initiatives alongside two senior data engineers
Participate in 24/7 on-call rotation (optional)
Technical Skills Required
Apache Kafka Kubernetes Python
Benefits & Perks
Flexible remote work within Germany or on-site in Cologne, Darmstadt, Düsseldorf, or Berlin
Relocation package for international hires
30 days of vacation per year and sabbatical options
Nice to Have
Object-oriented design and data modeling/dbt
BigQuery architecture expertise (access frameworks, partitioning, slot strategy)
Orchestration frameworks (Airflow, Dagster) or stream processing (Beam, Flink, Spark)
Internal automation tools (n8n, AI triage bots)
Terraform, Ansible, Pulumi, Helm, or other configuration management tools
Google Cloud Platform (GCP) experience

Job Description

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