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# Platform Engineer

- **Company:** Acuity Analytics
- **Location:** München, Germany
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Application Lifecycle Management, Automation of Tests, Microsoft Azure, Continuous Integration, Data Infrastructure, DevOps, Django Web Framework, Python (Programming Language), Key Management, Software Engineering, Cloud Platform System, Flask (Web Framework), Fastapi, Containerization, Kubernetes, Machine Learning Operations, Docker, Databricks
- **Published:** September 12, 2026
- **Apply:** https://startup.jobs/senior-platform-engineer-acuity-analytics-9994471

## About the Role

* Expert-level Python development skills.
 * Proven experience delivering production-grade APIs.
 * Strong DevOps background, including CI/CD implementation and automation.
 * Solid knowledge of containerization (Docker) and orchestration (Kubernetes).
 * Experience with ModelOps practices, tools, and frameworks.
 * Experience in cloud environments, ideally Microsoft Azure.

Nice to Have

 * Hands-on experience with Azure DevOps, Azure Container Registry, and Azure Key Vault.
 * Experience with Databricks or other modern data platforms.
 * Background in CI/CD and ModelOps for complex applications, including automated testing and deployment.
 * Familiarity with MLflow or similar tools for tracking, registry, and reproducibility.

## Description

We are seeking an experienced Senior Platform Engineer with deep expertise in Python development, DevOps, and ModelOps. You will be responsible for designing, building, and optimizing a modern platform on Databricks, ensuring robust deployment, monitoring, and governance of applications and services. This role blends software engineering, cloud-native architecture, and operational excellence in managing application lifecycle processes. You will collaborate with cross-functional teams to deliver scalable, reliable, and high-performance platform capabilities., * Design, develop, and maintain robust APIs using frameworks such as Flask, FastAPI, or Django.

 * Implement and manage CI/CD and ModelOps pipelines for streamlined deployment, monitoring, and governance.
 * Develop and deploy containerized applications using Docker and Kubernetes.
 * Operate within a cloud-native environment (preferably Azure) to deliver secure and scalable solutions.
 * Ensure reproducibility, traceability, and compliance in application lifecycle management.


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