Platform Engineer – Self-Service Data Platform

This is a fully remote position, open to applicants in Germany.

📋 Description

• Take charge of the data and storage self-service infrastructure.

• Design and sustain the storage architecture and access tools for extensive, multimodal biological datasets.

• Develop platform services that simplify complexity.

• Establish internal services and paved pathways that encourage self-service data access and processing.

• Work adeptly with object storage solutions (e.g., S3) and contemporary storage formats.

• Contribute to Infrastructure-as-Code (IaC) and Continuous Integration/Continuous Deployment (CI/CD), enhancing the team's Terraform/IaC and pipelines.

• Incorporate security measures into the data layer by implementing access control, data classification, and least-privilege access in code.

• Determine what transitions into the platform and what remains experimental.

⛳️ Requirements

• Experience in production platform or infrastructure (generally 3–5+ years) with a strong sense of ownership.

• Expertise in Infrastructure-as-Code, particularly with Terraform, along with hands-on experience with Kubernetes/Helm and containers.

• Knowledge of data platform capabilities, including a solid understanding of object stores, relational databases, modern storage formats, and the data workflows built on top of them.

• Familiarity with data/workflow orchestration tools (e.g., Dagster, Airflow, Prefect).

• Strong software engineering skills in Python (or a comparable language suitable for data and platform work) with robust engineering practices.

• Security-conscious engineering approach — implementing access control and least-privilege in code rather than as an afterthought.

• A platform-as-a-product perspective — creating self-service capabilities that users find valuable, enabling rather than obstructing.

🏝️ Benefits

• Flexible and remote-friendly work options.

• Ample opportunities for growth at the intersection of AI and biology.