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- Tasks: Lead data governance efforts, ensuring datasets are FAIR and compliant.
- Company: Join a dynamic team focused on scientific computing and data management.
- Benefits: Enjoy hybrid work options and a collaborative environment.
- Why this job: Make a real impact in R&D while building scalable governance foundations.
- Qualifications: 5+ years in data management or governance; familiarity with FAIR principles required.
- Other info: Ideal for those who thrive in fast-paced, evolving environments.
The predicted salary is between 36000 - 60000 £ per year.
Data Governance LeadLocation: Hybrid (London or Remote, UK-based preferred) Team: Data & Scientific Computing Type: Full-time, Individual ContributorThe OpportunityWe’re looking for a Data Governance Lead to scale our internal data governance practice. You will work cross-functionally with data scientists, ML engineers, software developers, and wet lab scientists to ensure our datasets are FAIR (Findable, Accessible, Interoperable, Reusable), compliant, and scientifically valuable.This is a hands-on, individual contributor role — ideal for someone who thrives on structure, clarity, and pragmatic problem-solving, and is excited by the challenge of building scalable governance foundations in a fast-moving R&D environment.What You\’ll DoDesign and implement standards for metadata, documentation, structure, format, and data ownership, ensuring alignment with FAIR principlesCoordinate data stewardship efforts across scientific and technical teams (e.g., Data Science, Machine Learning, Wet Lab, Discovery)Lead the development and adoption of the internal data catalogue, enabling discoverability and traceability of datasetsSupport no-code exploration tools to empower scientists and lab users with intuitive data accessBuild robust documentation and governance workflows for versioning, data lineage, access, and retentionTranslate regulatory and licensing requirements into actionable workflows and policiesPromote best practices for data compliance, quality, and reusability across teamsWhat You\’ll Bring5+ years’ experience in scientific data management, data governance, bioinformatics, or data engineeringDeep familiarity with FAIR principles, metadata standards, and data catalogue toolsProven ability to work cross-functionally with technical, scientific, and operational teamsHands-on experience with modern data workflows (e.g., Python, data lakes, notebooks, versioning)Understanding of scientific data lifecycles — from generation and ingestion to curation and archivingComfortable operating as an individual contributor, with strong ownership and autonomyBonus PointsExperience implementing no-code/low-code solutions for scientific usersFamiliarity with compliance frameworks (e.g., data licensing, GDPR, IP/data rights in scientific settings)Exposure to knowledge management systems and internal data enablement initiativesWho You AreThoughtful communicator and effective collaborator across disciplinesStructured, pragmatic, and hands-on — with a natural drive to bring clarity to complex systemsComfortable in ambiguous or evolving environmentsUser-focused, feedback-driven, and motivated to make data truly usable and impactful
Omics Data Governance Lead employer: LinkedIn
Contact Detail:
LinkedIn Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Omics Data Governance Lead
✨Tip Number 1
Familiarise yourself with the FAIR principles and how they apply to data governance. Being able to discuss these concepts confidently during your interactions will demonstrate your expertise and alignment with our goals.
✨Tip Number 2
Network with professionals in the data governance and scientific computing fields. Attend relevant webinars or conferences to connect with potential colleagues and gain insights into current trends and challenges in the industry.
✨Tip Number 3
Prepare to showcase your experience with cross-functional collaboration. Think of specific examples where you've successfully worked with diverse teams, as this role requires strong communication and teamwork skills.
✨Tip Number 4
Stay updated on compliance frameworks like GDPR and data licensing. Understanding these regulations will be crucial for translating them into actionable workflows, which is a key responsibility of the role.
We think you need these skills to ace Omics Data Governance Lead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in scientific data management, data governance, and familiarity with FAIR principles. Use specific examples that demonstrate your ability to work cross-functionally and implement data standards.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background aligns with the responsibilities of the Data Governance Lead, particularly your experience with metadata standards and data catalogue tools.
Showcase Technical Skills: Mention any hands-on experience you have with modern data workflows, such as Python or data lakes. Highlight any projects where you've implemented no-code/low-code solutions, as this is a bonus point for the role.
Demonstrate Communication Skills: Since the role requires effective collaboration across disciplines, provide examples in your application that showcase your communication skills. This could include experiences where you successfully coordinated efforts between technical and scientific teams.
How to prepare for a job interview at LinkedIn
✨Understand FAIR Principles
Make sure you have a solid grasp of the FAIR principles (Findable, Accessible, Interoperable, Reusable). Be prepared to discuss how you've applied these principles in your previous roles and how they can be implemented in the context of the company's data governance.
✨Showcase Cross-Functional Collaboration
Highlight your experience working with diverse teams, such as data scientists, ML engineers, and wet lab scientists. Prepare examples that demonstrate your ability to coordinate efforts and communicate effectively across different disciplines.
✨Demonstrate Problem-Solving Skills
Be ready to discuss specific challenges you've faced in data governance or management and how you approached solving them. This role requires pragmatic problem-solving, so showcasing your thought process will be key.
✨Familiarity with Data Workflows
Brush up on modern data workflows, especially those involving Python, data lakes, and versioning. Be prepared to explain how you've used these tools in past projects and how they can benefit the company's data governance practices.