Informacje o stanowisku

For a pharmaceutical company were looking for an experienced Solution Architect to join clients product team focused. The ideal candidate will be instrumental in defining the technical vision, architecture, and design for our next-generation biosample tracking, inventory, and lifecycle management software applications. This role requires a strong blend of deep technical expertise, understanding of life science R&D processes, and excellent communication skills to bridge the gap between 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 in leveraging AI in data product development & delivery processes (e.g. spec-driven-development).
• Very good understanding of architecture principles of FAIR data, 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, 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.
• 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.

For a pharmaceutical company were looking for an experienced Solution Architect to join clients product team focused. The ideal candidate will be instrumental in defining the technical vision, architecture, and design for our next-generation biosample tracking, inventory, and lifecycle management software applications. This role requires a strong blend of deep technical expertise, understanding of life science R&D processes, and excellent communication skills to bridge the gap between product strategy, customer needs, and technical implementation

,[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., 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 Requirements: Python, ETL, SQL, Kubernetes Additionally: Sport subscription, Private healthcare, International projects.

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