Data & Digital Lead - Infrata
HybridLondon, England, United Kingdom
Job Summary
Design and lead the structuring of Infrata's project archive into a curated precedent and knowledge library, including taxonomy, metadata standards, and quality assurance processes. Establish and enforce data governance for the knowledge base, working with legal and compliance advisers on confidentiality, access controls, and retention policies. Steward proprietary analytical tools, build data pipelines for retrieval infrastructure, and evaluate pilots of new technologies like AI-assisted document review within group-approved platforms. Define success measures for pilots and translate proven workflows into standard delivery practice with training support for consulting teams. Collaborate with dss+ group IT and security teams to align the data roadmap with group architecture.
Required Qualifications
- Significant experience in data engineering, knowledge management, or applied data roles
- Proven track record structuring large volumes of unstructured content (reports, models, technical documents) into governed, searchable knowledge assets
- Hands-on experience with modern data tooling: Python or similar, document processing, search and retrieval systems, and cloud data platforms
- Practical experience deploying or piloting large language model and AI-assisted workflows in a governed corporate setting, including prompt design, evaluation, and human-in-the-loop review
- Experience working with information security, legal, and compliance stakeholders on data classification, confidentiality, and acceptable-use frameworks
- Strong data architecture and pipeline design capability
- Rigorous approach to data governance, confidentiality, and quality assurance
- Ability to translate between technical teams, consultants, and senior leadership
- Sound judgement on where automation adds value and where expert human review must remain in control
- Self-starting and comfortable operating without an established data function around you
- Degree in Computer Science, Data Science, Engineering, Mathematics, or a related discipline, or equivalent demonstrable experience
- Fluency in English
Desired Qualifications
- Experience within professional services, engineering consultancy, financial services, or another document-intensive, regulated environment
- Additional languages
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