IT Application Manager RDU IT - Digital… at AstraZeneca · Spain -…

Location: Barcelona | Hybrid working: three days per week in the office and two days from home

This role supports the delivery, governance, and continuous improvement of enterprise digital analytics and AI-enabled capabilities across AstraZeneca and Alexion. Working with business, IT, data, legal, medical, regulatory, and external partners, the role translates strategic priorities into scalable services, robust controls, and measurable outcomes. It applies responsible AI and supervised agentic enhancements to create a flexible, resilient, and demand-driven analytics operating model.

Typical Accountabilities

• Digital asset governance: Run day-to-day governance for website content, data lineage, taxonomy, tagging, metrics, metadata, approvals, versioning, reuse, and lifecycle management, ensuring regional compliance and consistent data quality.

• Strategy execution: Partner with business and IT stakeholders to translate enterprise web, digital analytics, and AI strategy into prioritised roadmaps, delivery plans, trackers, and decision-ready documentation.

• Compliance by design: Embed privacy, regulatory, promotional, security, transparency, consent, and auditability controls into reusable workflows, templates, checklists, and delivery standards.

• Responsible AI governance: Administer guardrails and review workflows for models, prompts, datasets, and vendors, including risk classification, human oversight, monitoring, approval evidence, and audit readiness.

• AI-enabled digital analytics: Use approved AI copilots and generative AI tools to accelerate discovery, analysis, reporting, experimentation, and decision support while protecting sensitive information and validating outputs.

• Agentic analytics enablement: Identify, design, pilot, and scale supervised agentic workflows for data retrieval, quality checks, analysis, insight generation, and stakeholder-ready outputs, with defined goals, approval points, exception handling, audit trails, and fallback procedures.

• Demand-driven process improvement: Identify bottlenecks and unmet business needs, redesign workflows through automation and reusable services, and dynamically prioritise capacity to improve speed, quality, resilience, cost, and user experience.

• Platform integration: Coordinate AI-enhanced capabilities across CRM, MLR/PRC, DAM, analytics/BI, CDP, and field platforms, maintaining interface catalogues, API specifications, release notes, and change records.

• Scaled delivery and adoption: Coordinate discovery, pilots, controlled rollouts, success measures, adoption playbooks, quarterly business reviews, training, and change communications.

• Vendor and partner management: Maintain scorecards, service levels, performance indicators, compliance and security evidence, governance reviews, and remediation actions aligned with strategic priorities.

• Data stewardship: Operate consent, identity, metadata, access-control, catalogue, quality, and regional data-sovereignty processes, including approval gates for AI use.

• Operational excellence: Maintain portfolio, budget, benefits, quality, compliance, and service dashboards; manage issue registers, telemetry, escalations, and resolution through measurable outcomes.

• Audit readiness and enablement: Maintain policies, procedures, model documentation, test results, approvals, and traceability; deliver onboarding, guidance, office hours, and feedback loops for safe and effective adoption.

Education, Qualifications, Skills and Experience

Essential

• Bachelor’s degree or equivalent experience in business, information systems, computer science, data, analytics, or a related discipline.

• Relevant experience in digital solution delivery, analytics operations, governance, or programme delivery within a regulated, global organisation.

• Demonstrated use of approved AI tools to improve individual and team productivity, including effective prompting, reusable workflows, output validation, information protection, and responsible adoption.

• Practical understanding of agent orchestration, tool and API integration, workflow state, evaluation, observability, exception management, and human-in-the-loop controls.

• Experience translating business demand into prioritised analytics improvements and measurable outcomes.

• Knowledge of privacy, data protection, compliance-by-design, audit, and data-governance practices.

• Working knowledge of digital platforms such as CRM, DAM, MLR/PRC, analytics/BI, and CDP, including interfaces and release coordination.

• Strong analytical, organisational, stakeholder-management, written communication, and documentation skills.

• Track record of continuous improvement, curiosity, innovative thinking, and confident delivery through ambiguity and change.

Desirable

• Experience in pharmaceutical, healthcare, or another highly regulated industry.

• Certifications or formal learning in AI governance, privacy, compliance, analytics, project management, or process improvement.

• Experience with model and prompt lifecycle management, monitoring, drift and bias controls, model documentation, and responsible AI oversight.

• Experience managing vendors, service levels, performance indicators, third-party risk, and remediation plans.

• Experience with experiment design, baselining, A/B testing, adoption measurement, and benefits realisation.

• Experience creating procedures, templates, controls, training, and adoption materials for global teams.