Platform Engineer (m/f/d)

Responsibilities

We are representing a confidential energy-tech organization in München that is building platform infrastructure for real-time energy data processing across Europe. As Platform Engineer, you will own the event streaming backbone, backend services, and cloud infrastructure that the entire product depends on.

You will work on:

• Event streaming architecture using Kafka — topic and schema design, partitioning, retention policies, delivery semantics, managing consumer lag, replays, backfills, and handling late or duplicated readings from industrial meter sources
• Backend services in TypeScript that ingest data, integrate with third-party systems, and provide consistent APIs to product teams despite varying site configurations
• Cloud infrastructure on GCP including compute, networking, IAM, infrastructure as code, CI/CD pipelines, and observability tooling that enables self-service deployment and debugging
• Technical direction and platform standards — deciding where to invest, what to standardize, and how to balance platform maturity with product velocity

You will join a 12-person engineering team working in two squads, with direct ownership and rapid deployment cycles measured in weeks.

What We're Looking For

Must have:

• 6–8+ years building and running backend systems in production, including substantial platform or infrastructure work that other engineers relied upon
• Strong backend engineering experience in TypeScript — you have designed, shipped, and operated services and APIs in production, not merely used it for frontend work
• Hands-on production experience with Kafka: topic design, consumer groups, ordering and delivery guarantees, troubleshooting consumer lag at scale (comparable streaming platforms acceptable if you know them deeply)
• Solid cloud experience on GCP or equivalent: containers, networking, IAM, infrastructure as code, CI/CD, monitoring and alerting — you have owned infrastructure, not just deployed to it
• Comfort with high-volume time-series data: ingestion patterns, data quality challenges, backfills, and managing late, missing, or duplicated readings
• Production maturity — enough years to recognize which trade-offs create technical debt, when the boring option wins, and how to make decisions with incomplete information
• Kubernetes knowledge sufficient to run and manage clusters, not only deploy workloads
• Clear written and spoken English; German is a plus

Nice to have:

• Domain experience in energy, industrial IoT, or other sectors with hardware-generated data
• Exposure to metering protocols, device telemetry at scale, or streaming data pipelines
• Knowledge of a second language such as Python, Go, or Kotlin
• Experience with on-call responsibilities: monitoring, alerting, and debugging production issues

How We Work With You

Candidates apply through Get A Job.ai. Our talent team will conduct an initial screening to understand your background and confirm fit. We then submit qualified candidates to our client for their interview process. Please do not contact the client directly — all communication flows through our recruiting team to ensure a smooth process for everyone.

Pay

Pay and benefits are provided directly by the client and will be discussed during the interview process. Details will be shared once we advance your candidacy.

Equal Opportunity: Get A Job.ai is committed to inclusive recruiting practices. We welcome applications from candidates of all backgrounds and work to ensure fair consideration throughout the hiring process.