Software Engineer Python, DevOps, Data

We are seeking a Data Platform & Integrations Engineer to take end-to-end ownership of the data infrastructure, system integrations, and security posture behind a critical scientific screening data platform. In this role, you will ensure that data products flow reliably across environments (DEV, UAT, PRD), automate infrastructure and CI/CD pipelines, and maintain production stability for research and external partner workflows.

Key Responsibilities

• Data Integrations & Pipelines: Build, migrate, and maintain Information Links (ILs) and ETL/API integrations across DEV, UAT, and PRD for core data products (e.g., Sapio, Sample Validation, Bioregister, MOSAIC, PLATO).
• Platform & Cloud Infrastructure: Configure and maintain workspace environments (Onyx, CVO file shares, Data Publication App), service accounts, and underlying cloud infrastructure (Azure / GCP) using Terraform.
• Platform Enhancements (Spotfire / DFE): Deliver functional improvements and bug fixes within Spotfire / DFE (e.g., Fit Validation usability, workflow table optimization, large-file handling, Open Source R support).
• Security & DevOps Governance: Manage GitHub repositories, CI/CD pipelines (GitHub Actions, Azure DevOps), secret rotation, SSL certificate renewals, and vulnerability remediation (Dependabot alerts, LDAP hardening).
• Production Support & Troubleshooting: Investigate and resolve production incidents across data validation pipelines, historical datasets, and external CRO/partner data flows.
• Backlog & Delivery Planning: Own the operational backlog in Azure DevOps, breaking down technical enhancements into actionable PBIs and tasks.

Requirements (Must-Have)

• Programming & Scripting: Strong hands-on proficiency in Python for data integrations, automation, and backend tooling.
• Cloud & Infrastructure as Code: Practical experience operating in Azure and/or GCP environments, utilizing Terraform for infrastructure provisioning.
• DevOps & CI/CD: Solid experience with GitHub, GitHub Actions, and Azure DevOps (ADO), including repository governance, PBI-based delivery, and dependency vulnerability management.
• Data Integrations: Proven experience designing and maintaining data pipelines, APIs, and multi-environment deployments (DEV/UAT/PRD).
• Security & Production Operations: Hands-on knowledge of secrets/certificate lifecycle management, IAM/service-account roles, and production troubleshooting.

Nice-to-Have (Strong Assets)

• Direct experience with Spotfire / DFE, Denodo (data virtualization), or Sapio (LIMS / lab & screening data systems).
• Familiarity with R and scientific/R&D data workflows.