A World-Changing Company at Lifebit

At Lifebit, we're driven by the mission to make complex data analysis simpler and more accessible. We empower key institutions worldwide to revolutionize their data utilization and technology integration. Lifebit is powering the world's federated data platforms for population-scale health and life sciences. Our Federated AI Platform is trusted across national health systems, integral pharma, and research biobanks to unlock sensitive biomedical and real-world data securely, compliantly, and at scale.

As we scale through our Series B growth phase, we are expanding our product organization to meet the demands of a global market. Join us if you're inspired to tackle meaningful challenges and want to lead the next generation of health technology and cloud-based genomic solutions.

As a Data Science Engineer in our Spain hub, you will bridge the gap between complex biological science and robust software engineering. You will be responsible for building the scalable infrastructure that powers our scientific discoveries, ensuring that our data pipelines are not only high-performing but also strictly compliant with European data protection standards.

This is a senior individual contributor (IC) role in our engineering framework — ideal for someone who thrives in complex problem-solving, leads implementations for major features, and mentors others in technical excellence.

You'll work with distributed systems, APIs, and data services that underpin Lifebit's products — ensuring performance, security, and reliability at scale. Design software with built-in resilience and observability; balance immediate product delivery with long-term platform sustainability.

Champion engineering best practices, including test automation, CI/CD, and high code quality standards.

Cross-Functional Sync: Collaborate with Product, Science, and DevOps to define milestones and ensure projects move from conception to production with measurable impact.

Incident Management: Lead root cause analysis (RCA)



for live incidents and implement permanent structural solutions.

Stakeholder Management: Communicate technical concepts effectively to a diverse audience, ranging from cloud engineers to molecular biologists.

Mentorship: Provide guidance and peer feedback to junior and mid-level engineers to foster a culture of continuous learning.

Data & Domain Awareness

Apply your background in bioinformatics or computational biology to ensure solutions align with genomics or clinical data use cases.

Build systems that protect sensitive biomedical data, adhering strictly to GDPR (RGPD in Spain), HIPAA, and ISO***** standards.

Expert in designing biomedical knowledge graphs and semantic data models that make implicit relationships in biomedical data explicit and machine-interpretable for LLMs and AI agents to reason over at scale.

Hands-on experience integrating large language models into data systems, building RAG (Retrieval-Augmented Generation) frameworks, and architecting systems where rich metadata, lineage, and business semantics are embedded to enable reliable AI reasoning.

Modern Data Fabric Architecture

: Proven expertise designing data fabrics and federated data models that connect distributed biomedical data sources (genomics, clinical, imaging, drug discovery) while maintaining provenance, governance, and optimizing for AI/ML workload consumption—not traditional human dashboards.

Education: MSc in Computer Science, Bioinformatics, Computational Biology, or a closely related advanced technical field.

Experience: 5+ years in software engineering or computational systems development, preferably in data-heavy or regulated sectors.

Tech Stack: Strong programming skills (Python, Go, Java, or similar)



and familiarity with microservice or distributed system architectures.

Infrastructure: Proven experience designing and maintaining production-grade systems (preferably in data-heavy or regulated environments). Hands-on experience with cloud platforms (AWS, Azure, or GCP), CI/CD pipelines, and container orchestration (Docker, Kubernetes).

Data & Security: Working understanding of data privacy, observability, and security principles.

Experience working with life sciences or healthcare data (e.g., Familiarity with data harmonization, metadata catalogs, or scientific workflow orchestration.

Experience mentoring engineers or leading code quality initiatives.

Our mission-driven organization is dedicated to making a significant impact in science and healthcare. performance-based bonus.

AI Upskilling: Use up to £10,000 and 10 dedicated days per year for qualified AI-related professional development (AI certification, LLM workshop, or AI bootcamp).

Professional Development & Wellbeing: An annual personal development budget of £1,000 for conferences, training, certifications and personal wellbeing.

Remote-First Culture: Work from anywhere in Spain with a home-office stipend.

Flexible Working: Receive 25 working days of annual leave plus public holidays and flexible hours to maintain a healthy work-life balance.

Diverse Team: Join an international and diverse team passionate about transforming healthcare through data.

Deep Technology & Science: Get exposure to problems and applications in the cloud, data analysis, ML, life sciences, and big data fields.

Our fully remote model is built on trust and asynchronous communication, utilizing virtual workshops and occasional off-sites to maximize creativity and innovation.

In compliance with the Estatuto de los Trabajadores and Ley ******* guidelines, we ensure transparent pay structures and robust data privacy for all staff.

Join us in reshaping the future of data analysis and technology integration.

📌 Senior Azure Data Architect - Remote Work (Laza)
🏢 Lifebit
📍 Laza