Programme / Project management - Principal

Title: Programme / Project management - Principal
Work Location: CCW-S borg
Work Location Address: stmarken 3A
Start Date: 8/31/2026

Job Description:
IMPORTANT: We are seeking candidates across both DK (S borg) and UK (London)
Why this role exists
Novo Nordisk R&D is preparing a bounded, six-month acceleration to establish a governed, AI-ready data foundation for priority R&D data. The intent is that a business user, such as a clinical trial manager or a scientist can ask a single question and discover relevant data across cohorts, clinical trials, omics and imaging without stitching sources together by hand, and that approved AI agents can retrieve that data safely, with meaning and provenance attached. The programme is deliberately scoped to R&D and to an agreed set of priority data products rather than to the whole data estate.
The defining characteristic of the programme is that it is not a greenfield build. A great deal already exists: a data catalogue, governed access services, ontology management, domain knowledge graphs, active data science acceleration and early agentic initiatives. That capability has grown up in different teams, under different sponsors, with different definitions and uneven governance. The gap is not the absence of capability; it is the absence of a single, shared and well-governed direction for capabilities we already have.
The largest determinant of success is therefore not engineering throughput. It is the ability to find the work that is already underway, connect it, identify any gaps to address, agree one definition of done with owners who do not report to each other, and then hold that alignment for six months under real delivery pressure. We are seeking an experienced external programme manager to lead precisely that.
Purpose of the role
The Programme Manager leads the AI-ready Data Foundation programme end to end: first through a short readiness phase that converts assumptions into confirmed scope, delivery milestones, resources, governance and baselines, and then through six months of delivery against a plan that is measurable, testable and openly reported.
The role is defined as an integrator, connector and an 'engine' to move tasks forward rather than a builder. Success means that by month six several initiatives that were previously separate are demonstrably pulling in the same direction, that a small number of named scientific use cases can show measured before-and-after evidence, and that the organisation has a defensible basis for deciding what happens next.
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Please read through the attached job description document for more details.

Mandatory Skills:
At least eight years delivering complex data, digital or technology programmes, including three or more years at full programme level across several parallel workstreams and roughly twenty contributors at peak.
A demonstrable record of consolidating existing, independently sponsored initiatives into a single governed programme.
This is the most heavily weighted criterion, and candidates should expect to evidence it with two concrete examples.
Experience of enterprise data foundation work covering catalogue, governed access, metadata, business glossary, lineage, semantic or ontology layers and data ownership models.
Sufficient technical literacy in modern lakehouse and catalogue platforms, for example Databricks and Unity Catalog or equivalent, to challenge estimates, sequencing and architectural claims without needing to build.
Delivery experience under GxP or a comparable regulated validation regime, with quality assurance embedded from the start rather than applied at the end
A track record of establishing baselines and evidencing benefit, not only of reporting milestones.
Experience of operating in a matrix organisation where most delivery capacity is borrowed and the programme leads by influence rather than line authority.
Working familiarity with artificial intelligence, machine learning and agentic delivery, sufficient to govern that workstream credibly.
Experience running a sourcing critical path for scarce specialist skills, with fallback options prepared in advance.
Excellent communication skills. Fluent professional English and comfort working across international, multi-site teams. Pharmaceutical or life-science R&D exposure across clinical, omics or imaging data.
Familiarity with FAIR data principles and data certification frameworks.
Experience sourcing or managing knowledge-engineering and ontology specialists. Experience of a two-in-a-box operating model alongside an internal counterpart.
Working experience from either Denmark or UK.
Prior experience of handing a programme over to a permanent internal owner at the end of an engagement.