Independent Consultancy - Technical Planning and Coordination

Accountabilities

Consortium coordination and stakeholder engagement: Facilitate collaboration across five partner organizations by preparing meeting agendas, guiding technical discussions, documenting decisions, and building consensus among stakeholders with different priorities and working practices.
Needs assessment and user research: Interview data leads to assess existing datasets, systems, workflows, and user requirements. Help define priority audiences, use cases, access patterns, and the tools and assurances required by different user groups.
Technical project management: Develop and maintain an integrated workplan covering milestones, dependencies, responsibilities, and deliverables. Monitor progress, manage risks and action items, and coordinate regularly with the consortium's secretariat and technical leadership.
Data mapping and interoperability: Create a centralized inventory of datasets, data collection tools, and internal data assets across participating organizations. Identify gaps, overlaps, and opportunities to improve integration and reuse.
Standards and documentation: Develop proposals for shared data schemas, identifiers, metadata standards, validation processes, and machine-readable documentation. Establish a framework for linking records across organizations through jointly governed identifiers and crosswalks.
Platform architecture and technical recommendations: Evaluate hosted, federated, and hybrid architecture options, taking into account different data products, version control, data provenance, reproducibility, and integration requirements. Recommend shared protocols and a practical technical architecture.
Data hub proof of concept: Define the requirements and scope of a limited proof of concept demonstrating how a shared platform could serve selected user groups. Coordinate the handover of requirements and assess the resulting prototype, which will be developed by external data engineering contractors.
AI-ready energy data strategy: Contribute to approaches for making trusted energy datasets accessible and discoverable by AI systems, including through structured metadata, APIs, and other machine-readable interfaces. Support knowledge exchange on AI-assisted research methods.
Roadmap development and reporting: Co-author the consortium's final plan with participating organizations, producing an implementation-ready technical and governance roadmap for the next phase. Deliver regular progress reports, meeting documentation, and agreed technical deliverables.
Requirements
Minimum qualifications
At least 8 years of professional experience in data architecture, data management, or data product development, preferably within the energy or climate data sectors.
Demonstrated experience facilitating and managing technical projects, working groups, or collaborative initiatives involving multiple organizations.
Strong English communication skills, with the ability to lead discussions, synthesize complex technical information, and document decisions and recommendations clearly.
Preferred qualifications and skills
Strong stakeholder facilitation and consensus-building skills, particularly in environments where organizations have different technical practices, priorities, and governance structures.
Hands-on experience with data integration and interoperability, including common schemas, identifiers, entity resolution, metadata standards, and data documentation.
Familiarity with open energy data ecosystems, open-source energy modeling tools, reproducible data pipelines, and collaborative research infrastructure.
Knowledge of data platform architecture, including hosted, federated, and hybrid models, as well as versioned data releases, APIs, and data provenance practices.
Understanding of how AI systems access and interpret structured data, including machine-readable metadata, APIs, and Model Context Protocol (MCP) servers.
Experience working with open-source, open-data, digital public goods, research, or other mission-driven organizations, including an understanding of data stewardship, licensing, and governance.
Strong analytical, organizational, and project management abilities, with the capacity to translate complex technical concepts into actionable plans and deliverables.
Based in Europe to facilitate time zone alignment with consortium members. Eligibility to work as an independent consultant will be assessed in the country where the services are performed before a contract is offered.
Benefits
Competitive consultancy budget: Approximately US$135,000 allocated to the assignment, with fees paid on a time-and-materials basis at an agreed hourly or daily rate.
Remote working arrangement: Work remotely while collaborating with an international network of energy data and research experts.
Flexible schedule: Organize your working hours independently around agreed milestones and mutually scheduled meetings, with an estimated commitment of approximately 20 hours per week rather than a fixed weekly schedule.
Meaningful impact: Help shape open, publicly accessible energy data infrastructure designed to improve research, policy analysis, and evidence-based decision-making.
Technical and strategic influence: Contribute directly to decisions on data interoperability, platform architecture, shared standards, and AI-ready energy intelligence.
International collaboration: Work across five organizations in a multidisciplinary environment spanning data engineering, energy research, modeling, and open-source technology.
Professional autonomy: Operate as an independent consultant, with responsibility for your own working arrangements and delivery approach.
Clear project structure: Work against an agreed inception plan, defined deliverables, milestones, review responsibilities, and acceptance criteria.
Contract and application details
Expected start: Mid-December 2026, subject to agreement.
Duration: 12 months from the agreed start date.
Application deadline: November 11, 2026.
Required application materials: CV or résumé, cover letter, one or two examples of relevant work, and a proposed hourly or daily rate in US dollars. Daily rates should specify the number of hours included.
Cover letter: Briefly describe your relevant experience in data integration, interoperability standards, and multi-organization facilitation; your availability and earliest start date; and your location and time zone.
Work samples: Examples may include data architecture proposals, interoperability frameworks, technical roadmaps, or collaborative reports. Explain your contribution and provide links or anonymized excerpts without disclosing confidential information.
Additional selection steps: References may be requested from shortlisted candidates. Interviews, clarification requests, and negotiations on the final scope and contract terms may also form part of the selection process.