Backend Data Engineer (Python/dbt)

Location: Remote within France, with regular team time in Biarritz.

Company

hirify.global develops medical remote monitoring solutions for oncology, gastroenterology and psychiatry, using ePRO collection and AI techniques to improve patient care and support clinical research.

What you will do

• Build backend features for the Research Data Platform using Python, FastAPI and PostgreSQL.
• Build and maintain dbt models, including business logic, tests, documentation and repository standards.
• Collaborate with Research, Clinical, Business, Product and Engineering stakeholders to deliver data solutions.
• Contribute to code reviews, technical design and continuous improvement of engineering standards.
• Support BI solutions such as dashboards and business analysis.
• Develop semantic-layer metrics governance and automate reporting, quality triage and source onboarding with responsible AI usage.

Requirements

• Approximately 3–5 years of experience across data and software, typically as an analytics engineer moving toward software engineering.
• Production-grade Python skills, including tests, code quality, code reviews and CI.
• Experience building and maintaining backend APIs with FastAPI, Flask, Django or an equivalent framework.
• Advanced SQL and experience delivering production dbt models with documentation and tests.
• Experience with Git workflows, pull requests and maintained codebases.
• Experience with self-service data tooling, enablement and collaboration with product or engineering teams on data topics.
• Ability to deploy and operate software using containers, environments and CI/CD, and to implement data tests, alerting and data-quality troubleshooting.
• Structured, detail-oriented and automation-focused approach, with ownership, autonomy, accountability, pragmatism and clear communication.
• Experience working in high-standard environments involving security, compliance or sensitive data.

Nice to have

• Experience with semantic layers or metrics governance, such as Cube.js, LookML or dbt Semantic Layer.
• Healthcare data experience or work in other GDPR-heavy environments.
• Experience supporting scientific users with tools such as Jupyter or RStudio.

Culture & Benefits

• Remote-friendly work setup for a small three-person Data & Analytics team.
• Direct exposure to product, research and clinical questions, with a culture focused on quality, ownership, automation and continuous improvement.
• Regular team seminars and meetings in Biarritz, including outdoor activities.
• The role combines backend engineering and modern data engineering, with practical AI usage.

Hiring process

• 15-minute Talent Acquisition screening, followed by a 45-minute manager-fit interview with Jean-Baptiste Pajot.
• Technical case study requiring up to 2 hours of preparation and a 1.5-hour live discussion, covering analytics engineering and software engineering.
• Further clinical-fit, culture-fit and strategic-fit interviews with research, medical, talent and engineering stakeholders.