Platform Engineer
Position Overview As a Platform Engineer within the Integration & Platform team, you are responsible for building, operating, and continuously improving integration and platform capabilities that are used by multiple development teams across the enterprise.
The role focuses on platform stability, automation, self-service, and end-to-end operational responsibility ("you build it – you run it"). This position is centered around Kafka cluster & HiveMQ administration and the automation of related management tasks, ensuring reliable operation and scalability of the messaging platforms. While the position is not focused on daily application development, you are expected to participate in customer and internal domain projects when needed.
Responsibilities
- Design, deploy, and maintain multi-cluster, multi-region Apache Kafka environments managed by the Strimzi Operator or similar on Kubernetes, as well as enterprise HiveMQ MQTT brokers.
- Drive the platform upgrade lifecycle (minor and major versions) for Kafka, Strimzi, and HiveMQ, coordinating platform patching cadences seamlessly to mitigate CVEs with zero application downtime.
- Develop and maintain custom Kafka Connectors (Source/Sink) for seamless data movement between legacy systems and the cloud.
- Formulate and implement scaling strategies, node affinity rules, topology spread constraints, and persistent volume management optimized for IOPS-intensive message workloads.
- Manage Kafka broker partition layouts, topic compaction configurations, segment retention behaviors, and cluster-wide resource allocation.
- Design high-availability and disaster recovery strategies, including cross-region replication and automated failover, to maintain platform resilience as usage scales.
- Enforce data governance standards through the management of Schema Registries (Avro, Protobuf, JSON Schema).
- Architect edge traffic routing to messaging clusters using advanced ingress layers, translating complex routing policies and managing edge capabilities like Envoy Gateway or custom proxies.
- Enforce data governance boundaries by implementing Kafka ACLs, SASL authentication structures, and integrating API Managers for authentication intercept handles (e.g., managing OAuth/OIDC validation paths).
- Implement robust end-to-end security frameworks, including mutual TLS (mTLS) validation, SSL verification, SASL/SCRAM, and RBAC for the platforms.
- Build and maintain deep observability pipelines using Prometheus and Grafana, configuring custom dashboards to monitor critical broker KPIs.
- Formulate proactive alerting rules to catch cluster anomalies—such as KubeNodeNotReady, JVM memory degradation, disk capacity thresholds, or storage detached states—before they impact production workloads.
- Perform Root Cause Analysis (RCA) for platform outages and implement automated guardrails to prevent recurrence.
- Provide Tier 3 support for complex integration issues, such as consumer lag, rebalance loops, or network bottlenecks.
- Act as a technical subject matter expert (SME) for application engineering teams developing in Java / Spring Boot, advising on optimal Producer/Consumer settings (e.g., acks, idempotency, batch sizing, schema management).
- Ensure stability, performance, scalability, and cost efficiency across all integration services.
- Architect and maintain reusable GitHub Actions CI/CD pipelines to validate, lint, and test infrastructure manifests, Kafka client configurations, and custom plug-ins prior to deployment.
- Utilize automated scaling frameworks like KEDA (Kubernetes Event-driven Autoscaling) to dynamically scale application consumers based on real-time lag and throughput metrics.
- Treat infrastructure strictly as code by leveraging Helm for packaging, resource templating, and managing OCI artifacts.
- Provide clean abstractions, developer self-service tooling, and documented READMEs to empower development teams to provision topics, schemas, and credentials safely within architectural guardrails.
- Handle incident, problem, and change management at the platform level.
- Collaborate closely with Enterprise Security, Architecture, and core software engineering teams across the organization.
Personal Attributes:
- Strong analytical and problem-solving skills.
- Humble attitude with a collaborative mindset.
- Comfortable with end-to-end operational responsibility.
- Fluent in English (Swedish is an advantage).
Krav
Platform & Cloud:
- 4–6 years of experience with Apache Kafka, Strimzi, Kafka Connect API, and KRaft.
- 4–6 years of experience working with Java and the Spring Boot Framework.
- Experience with PostgreSQL.
- Strong hands-on experience with Azure Kubernetes Service (AKS).
- Solid Linux experience (including WSL).
- GitHub Actions and ArgoCD experience.
- Knowledge of Splunk, Fluent Bit, and Helm.
DevOps & Automation:
- CI/CD pipeline automation using GitHub Actions and/or Jenkins.
- Infrastructure as Code (Terraform or equivalent).
Observability:
- Splunk, Grafana, and Prometheus.
- Fluent Bit or OpenTelemetry.
Streaming & Messaging:
- Apache Kafka at an enterprise platform level (clusters, performance tuning, security).
- Enterprise HiveMQ broker administration.
Meriterande
Nice to Have:
- Experience with APIM (API Management) platforms.
- Multi-cloud experience (Azure, AWS, or Google Cloud).
- Cloud cost optimization experience.
- Experience working within an Integration or Core Platform department in a large enterprise environment.