Advancing Analytics

• Own and manage the organisation's core business systems (SharePoint, Miro, HubSpot, PandaDoc and others), including configuration, user life-cycle, integrations and compliance posture • Define and enforce access control policies, role-based permissions and joiner/mover/leaver procedures across all platforms, including conducting periodic access reviews • Develop and operationalise compliance-aligned processes including data retention, GDPR obligations and audit-readiness activities • Build and maintain standard operating procedures for system lifecycle events (new system onboarding, configuration changes, project creation, team changes, leavers, etc.) • Ensure systems governance and ownership processes across the organisation are forward-compatible with future ISO 27001 and SOC 2 compliance efforts • Act as the single point of accountability for system governance, working with stakeholders across the business to keep controls practical and proportionate • Maintain controlled documentation for system configuration, compliance procedures and information handling • Lead the compliance and governance evaluation when new tools or systems are introduced, ensuring they meet organisational standards before adoption • Own vendor risk assessment for SaaS and third-party platforms, including due diligence on security posture, data handling and contractual compliance • Set technical and governance guardrails for business-built tools, low-code applications and internal prototypes — giving teams safe paths to build and ship without creating shadow IT or orphaned systems • Provide data-boundary clarity for Client on-boarding, Change Management, Disaster Recovery and Business Continuity workstreams

• Design and document end-to-end data and AI solutions using Azure, Databricks, and related services. • Translate business and technical requirements into clear architecture designs that delivery teams can build. • Identify technical risks early, own them on the project risk register and be accountable for their mitigation and resolution. • Shape and guide the design of intelligent data platform projects using Lakehouse architectures, making data available for reporting, AI, and analytics. • Get involved early in client conversations to qualify opportunities and recommend the right approach. • Capture requirements, current state, workloads, governance constraints, and target outcomes. • Own the technical content of RFP and RFI responses, proposals, architecture diagrams, and Statements of Work. • Build strong relationships with clients and become a trusted technical advisor. • Take complex technical concepts and translate them into plain language and clear business outcomes for senior business leaders, technology leads, and internal sales teams.

• Collaboratively design Gold-layer data models • Conceptualise and deliver data strategy advisory services to clients • Deliver high-quality solutions that drive business value • Communicate effectively with customers and internal stakeholders • Build strong relationships with clients

• Support the roll out and maintenance of a large, federated, multi-service Data and AI platform • Focus on building secure, scalable, and cost-optimised cloud infrastructure • Implement governance and enable advanced data services

• Help build AI on a solid, reliable Data Platform • Collaborate with clients and team members to deliver projects • Lead projects while balancing technical and pragmatic needs • Engage in requirements gathering and client consulting

• Help customers implement a large language model, geared to solving complex and advanced business challenges. • Deploy an end-to-end ML pipeline to streamline and automate the AI offerings of some of the largest organisations in the world.