Senior Solution Architect

Responsibilities:

• Architect & design solutions to accelerate drug development through digitalization of the 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 taking into account organizational constraints
• 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 various product components in accordance with enterprise guidance
• Create and maintain architectural documentation, including system diagrams, data flow models, and technical specifications
• Ensure the architecture adheres to relevant regulatory standards (e.g., GxP, FDA 21 CFR Part 11) and industry best practices
• Act as the primary technical point of contact for the product Core Team, engineering team, Vendors, other products' stakeholders, and external stakeholders
• Collaborate closely with Product Management to define the technical roadmap and technical debt strategy. Strong focus on business outcomes
• Develop architecture knowledge by participating in:
  • Relevant product ceremonies,
  • Architecture governance bodies,
  • Domain Architecture Community,
  • Product & Technology related events
• Work with Validation and DevOps teams to ensure testability, automation, and operational readiness of the platform
• Conduct architectural reviews and technical design evolutions and approvals
• Design and govern AI for biosample data products, ensuring reproducibility, versioning of models, and traceability of data
• Define the technical strategy for integrating Large Language Models (LLMs) and Generative AI components responsibly within the Biosample Management product ecosystem
• Ensure compliance with internal AI governance frameworks, data privacy regulations (e.g., GDPR, FDA, HIPAA-related principles), and ethical guidelines for all AI-driven features
• Engage with potential and existing customers (e.g., lab scientists, biobank managers, IT personnel) to understand their biosample management challenges and gather technical and non-functional requirements
• Assist in troubleshooting complex technical issues that require deep system knowledge
• Work closely with enterprise architects in the domain to architect the solutions according to the enterprise standards
• Work closely with other solution architects in the domain to architect the solutions which co-exist and fit in the domain's ecosystem

Requirements:

• 5+ years of experience as a Solution Architect, Technical Lead, or in an 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 in leveraging AI in data product development and delivery processes (e.g., spec-driven development)
• Very good understanding of architecture principles of FAIR data and Data Mesh
• Very good understanding of architecture patterns such as ETL, ELT, noETL, and 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)
• Proficiency in the following technologies:
  • Strong Python skills, specifically for building scalable backends and data processing pipelines
  • Hands-on experience with Kubernetes orchestration is essential. Several projects rely on it for scaling
  • Familiarity with Airflow, Spark or similar frameworks is a major plus
  • Proven ability to design and optimize schemas specifically for Snowflake, Oracle and MongoDB, balancing performance with complex data traceability
  • Extensive experience in ETL pipeline design for large-scale datasets
• Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences
• Strong analytical and problem-solving skills
• Ability to balance short-term delivery needs with long-term architectural vision
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• Deep domain knowledge of Biosample Management, LIMS (Laboratory Information Management Systems), 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 a regulated environment

Offer:

• Private medical care
• Co-financing for the sports card
• Training & learning opportunities
• Constant support of dedicated consultant
• Employee referral program