Solution Architect

For a pharmaceutical company, the role involves defining the technical vision, architecture, and design for next-generation biosample tracking, inventory, and lifecycle management software applications. The position requires deep technical expertise, understanding of life science R&D processes, and communication skills to align product strategy, customer needs, and technical implementation.

• 5+ years of experience as a Solution Architect, Technical Lead, or equivalent role in software development.
• Proven experience designing and delivering scalable, enterprise-level solutions.
• Proven experience in designing Semantic Web / Linked Data solutions.
• Proven experience leveraging AI in data product development and delivery processes.
• Very good understanding of architecture principles of FAIR data and Data Mesh.
• Very good understanding of architecture patterns: ETL, ELT, noETL, GraphRAG.
• Extensive experience in ETL pipeline design for large-scale datasets.
• Expertise in cloud platforms.
• Proficiency in data modeling and database technologies (SQL and NoSQL).
• Strong Python skills for building scalable backends and data processing pipelines.
• Hands-on experience with Kubernetes orchestration.
• Familiarity with Airflow, Spark, or similar frameworks is a major plus.
• Proven ability to design and optimize schemas for Snowflake, Oracle, and MongoDB.
• Deep domain knowledge of Biosample Management, LIMS, Data Pipelines, or Clinical Trial operations.
• Familiarity with industry standards and regulations relevant to life sciences (e.g., GxP, data privacy standards).
• Understanding of scientific data types, provenance tracking, and metadata management in regulated environments.

• Architect and design solutions to accelerate drug development through digitalization of biosample processes and provisioning of actionable data products.
• Define and evolve the end-to-end technical architecture and data model for the Biosample Management product, ensuring scalability, reliability, security, and performance.
• Translate business requirements and user stories related to biosample workflows and data flows into robust and practical technical designs.
• Evaluate and select appropriate technology stacks, cloud services, and integration patterns (e.g., APIs, message queues) for product components.
• Create and maintain architectural documentation, including system diagrams, data flow models, and technical specifications.
• Ensure architecture adheres to regulatory standards (e.g., GxP, FDA 21 CFR Part 11) and industry best practices.
• Design and govern AI for biosample data products, ensuring reproducibility, versioning of models, and traceability of data.
• Define technical strategy for integrating Large Language Models (LLMs) and Generative AI components responsibly within the product ecosystem.
• Ensure compliance with internal AI governance frameworks, data privacy regulations (e.g., GDPR, FDA, HIPAA), and ethical guidelines for AI-driven features.
• Engage with customers (lab scientists, biobank managers, IT personnel) to understand biosample management challenges and gather requirements.

• Sport subscription
• Private healthcare
• International projects