Infrastructure Engineer

About the Role
We are looking for a Infrastructure Engineer (Kafka) to own and operate the Kafka estate behind an event-driven integration platform, including its build, deployment, and monitoring infrastructure.
The mandatory requirements are 4+ years of hands-on production Kafka experience, strong Linux and Python scripting, CI/CD, Docker or Podman, infrastructure-as-code, and strong English communication skills.
What you will do
Own the Kafka estate — topic design and naming standards, partitioning and keying strategy, replication, retention and compaction policy, consumer group and offset management, quotas, and broker configuration and upgrades.
Ensure platform resilience and reliability — keep the integration platform available when the upstream vendor SaaS platform is degraded or unavailable, absorb traffic spikes without overloading it, and ensure events remain replayable and auditable through a correctly sized, configured and operated Kafka infrastructure.
Engineer the platform's delivery guarantees in practice: at-least-once and exactly-once semantics, idempotent producers, transactional writes where warranted, dead-letter topics, and self-service replay tooling for recovering from downstream failures.
Build streaming observability: consumer lag, queue depth, throughput and rebalance monitoring; end-to-end correlation-ID tracing across topics; dashboards, service level objectives and alerting.
Plan capacity, cost and retention for a durable log with regulatory audit retention requirements, and tune it as adoption scales across the firm.
Evaluate and integrate vendor-native streaming and change-data-capture mechanisms as the platform's ingress and egress paths mature.
Own and evolve the build and release pipeline — automated Jenkins pipelines producing packaged application installs for multiple enterprise Linux generations, signed container images, and generated documentation, promoted through internal artifact and image distribution services.
Operate the runtime estate: containerised deployments, integration gateway hosts, and the ongoing operating-system modernisation of that estate.
Engineer the infrastructure behind the platform's resilience and continuity — health detection, circuit breaking, and the reconciliation and monitoring that prove the platform recovers cleanly when the upstream vendor platform is degraded or unavailable.
Automate environment provisioning and configuration, and keep the configuration and asset inventory a genuine single source of truth.
Partner with the squad's Python developers on deployability, performance and cost; participate in change management and production support.
Must haves
Deep, hands-on production Kafka experience of at least 4+ years — this is the central requirement. Topic and partition design, consumer group mechanics, retention and compaction, replication, performance tuning, and troubleshooting lag, rebalances and delivery failures under load.
Practical understanding of event-driven delivery semantics: at-least-once versus exactly-once, idempotency, ordering guarantees, dead-letter handling and replay.
Strong enterprise Linux engineering and automation — shell plus Python scripting.
CI/CD pipeline ownership, ideally Jenkins declarative pipelines, with real artifact and release management experience.
Containers — Docker or Podman, OCI images — and container orchestration platforms.
Infrastructure-as-code and configuration management.
Observability tooling: log aggregation, metrics, alerting and SLO definition.
GenAI-assisted development — you actively use AI coding agents in your daily workflow, or are demonstrably keen to adopt them. We automate and build with these tools across the squad and expect everyone to be fluent in them.
Networking, TLS, secrets management and enterprise authentication (OAuth2).
A production operations mindset: incident response, capacity planning and change control.
Strong written and verbal communication, working with a global team.
Upper-intermediate English level.
Nice to haves
Kafka ecosystem depth: Kafka Connect, Schema Registry, Kafka Streams, MirrorMaker, or managed Kafka services.
Change-data-capture patterns and tooling.
Infrastructure supporting large commercial SaaS platforms, including integration gateway or connector servers.
Package and artifact distribution at enterprise scale.
Experience in a regulated environment — audit retention, data classification, formal build and operate governance.
Kubernetes; multi-region and high-availability design.
Perks
Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
Well-being & support: access local well-being programs and people-focused support tailored to your location

Work arrangement
Yes