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DevOps & Data Architecture Intern

CompraTica Empleos

EMP:Construction
Berlin
Tiempo Completo
Remoto
0 vistas

Descripción

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Heidi Systems **Heidi Systems is building the data infrastructure layer for buildings and energy

We help property owners and managers digitize metering, consumption data, reporting, and billing workflows in one of the largest and most outdated infrastructure markets in Europe.

We are looking for an exceptional intern who wants to work close to the core of our technical system: data architecture, DevOps, infrastructure, and backend tooling.

This is not a classic internship.

You will work directly on production-relevant systems, help shape our data infrastructure, and build tools that directly impact customers, internal operations, and the scalability of the company.

Tasks What you will work on Build and improve our data ingestion and processing infrastructure Work on backend services in Go and TypeScript Support the architecture of reliable data pipelines for meter, gateway, and building data Improve internal DevOps workflows, deployments, monitoring, and system reliability Work with configuration formats such as YAML and TOML Help structure, validate, and transform high-volume device and consumption data Build internal tools that make our operations faster and more automated Support debugging of real-world infrastructure issues across gateways, MQTT, APIs, and databases Work closely with the founding team on technical architecture decisions.

Requisitos

Who we are looking for We are looking for someone unusually strong, curious, and hands-on

You should be excited about infrastructure, data systems, and clean technical architecture.

You do not need to know everything already, but you should learn extremely fast, think from first principles, and enjoy solving hard technical problems.

You are a great fit if you: Have strong coding ability and a clear technical mindset Are comfortable working independently and taking ownership Care about clean systems, reliability, and scalability Enjoy working close to real-world infrastructure and messy data Are curious a.

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