
Platform Engineer – Self-Service Data Platform
Posted Jul 30

Posted Jul 30
This is a fully remote position, open to applicants in France.
• Take ownership of the self-service data and storage layer. Develop and maintain the storage architecture and access tools for extensive, multimodal biological datasets — ensuring provisioning, access, and lifecycle management is available as a self-service option.
• Create platform services that simplify complexity. Design internal services and paved pathways that facilitate self-service data access and processing, reducing the need for researchers and engineers to submit tickets for routine tasks.
• Manage storage and data infrastructure. Work adeptly with object storage solutions (e.g., S3) and contemporary storage formats (e.g., Parquet, Delta, Iceberg); develop sensible, reproducible data workflows where required by the platform.
• Contribute to Infrastructure as Code (IaC) and Continuous Integration/Continuous Deployment (CI/CD). Enhance the team's Terraform/IaC and pipelines to ensure the data platform is as reproducible and deployable as the rest of the platform.
• Integrate security into the data layer. Implement access controls, data classification, and least-privilege access in code — ensuring that sensitive data is inherently protected.
• Employ a product-oriented perspective. Collaborate with the platform team to determine which features transition into the platform versus remaining experimental.
• Experience in production platforms or infrastructure (typically 3–5+ years) with a strong sense of ownership.
• Expertise in Infrastructure-as-Code (IaC) — specifically Terraform — along with practical experience in Kubernetes/Helm and containers.
• Proficient in data platform capabilities — have a solid understanding of object stores, relational databases, and modern storage formats, along with the data workflows that teams develop on top of these systems.
• Familiarity with data/workflow orchestration tools, such as Dagster, Airflow, or Prefect.
• Strong software engineering skills — proficient in Python (or a similar language suitable for data and platform development), with a focus on sound engineering practices.
• Security-conscious engineering — you implement access controls and least-privilege access in code, treating it as a fundamental aspect rather than an afterthought.
• A platform-as-a-product approach — you create self-service capabilities that are appealing to users and promote enablement rather than obstacles.
• Competitive salary and meaningful equity
• Flexible/remote-friendly working arrangements
• Significant opportunities for growth at the convergence of AI and biology
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