Technical Expert for Automated R&D Lab Data Inventory(m/w/x)

Description

In this role, you will revolutionize R&D laboratories by designing a centralized Lab Data Inventory that ensures data accessibility and compliance. You will collaborate with scientists and tech teams to integrate digital solutions while leveraging AI and ML concepts.

Requirements

• •Expertise in AWS Cloud technologies
• •Expertise in DevOps practices and tools (GitHub Actions, Terraform)
• •Expertise in database technologies (e.g., SQL, NoSQL) and data integration techniques
• •Proficiency in at least one programming language (e.g., Python, Java, R)
• •Experience with API development and system integration
• •Proficiency in RESTful API design and implementation
• •Strong ability to learn new subject areas independently and efficiently
• •Strong communication skills with proven ability to effectively communicate with both technical and non-technical stakeholders at all levels of the organization
• •Experience with common Agile tools (e.g., Jira, Confluence)
• •Excellent team working skills with ability to collaborate effectively in cross-functional, international teams
• •Knowledge of laboratory processes and workflows in research and early development environments
• •Strong business analysis skills including requirements elicitation, documentation, and management
• •Ability to translate complex scientific requirements into technical specifications
• •Experience with Benchling, Signals (Revvity/PerkinElmer), Other ELN systems
• •Experience developing products with Agile methodologies a must
• •Master's or Bachelor's Degree in relevant field

Tasks

• •Design and build a central Lab Data Inventory for R&D lab data
• •Develop a comprehensive metadata schema for diverse R&D data types
• •Architect a scalable repository structure for current and future data needs
• •Implement governance protocols for data quality, security, and compliance
• •Design and build integration with Electronic Notebooks (ELNs)
• •Develop robust APIs and data pipelines for data flow between ELNs and the central catalog
• •Ensure data consistency and integrity across multiple platforms
• •Implement automated data extraction and loading (ETL) processes
• •Implement data discovery and analytics capabilities within the central catalog
• •Design and integrate search functionalities for efficient data retrieval
• •Develop dashboards and reporting tools for data visualization and analysis
• •Develop and maintain documentation for the Lab Data Inventory and integration processes
• •Create user guides, system architecture diagrams, and API documentation
• •Establish and document best practices for data management and integration
• •Ensure compliance with industry standards like GxP and GDPR
• •Develop and maintain documentation for GxP validation of systems
• •Collaborate with regulatory and compliance teams on requirements
• •Implement audit trails and data governance practices aligned with GxP
• •Implement data protection and access control measures
• •Collaborate with cross-functional teams to understand data requirements
• •Conduct regular stakeholder meetings to gather requirements and feedback
• •Translate scientific requirements into technical specifications
• •Continuously evaluate and implement emerging technologies in lab data management
• •Stay informed about advancements in data architecture and integration technologies
• •Propose and lead pilots for innovative data management solutions

Tools & Technologies