Director, Data Analytics

Description

The company is a UK pharmaceutical wholesale business, and this is a Data Leader role for its data and analytics function during a period of major change.

You will set the direction for the data and analytics capability and lead the team that delivers it, while legacy systems are being replaced at scale.

The target technology stack centres on Azure, Databricks and Power BI.

The role combines strategy with hands-on delivery accountability: a forward-looking data roadmap, the team that builds it, and stronger data governance across the organization.

You will turn the enterprise data and analytics strategy into concrete results and look beyond current priorities. A key part is finding and embedding AI across data work to speed up and improve output, and to help the business improve operations, customer outcomes and competitive position.

Governance is central. You will strengthen policies, ownership, tooling and culture so that data is trusted, secure and compliant, pacing change to what the business can absorb.

You report to the Senior Director, Analytics & Data Management.

Experience in healthcare or pharmaceutical wholesale would be an advantage.

Responsibilities

• Strategy and roadmap: define and own a multi-year data and analytics roadmap for the UK business, aligned to the enterprise strategy and refreshed as priorities change.
• Turn strategy into a prioritized, sequenced and costed set of initiatives with milestones, dependencies, trade-offs and measurable outcomes.
• Advise senior leaders on emerging data and AI trends, platform direction, and the opportunities and risks these bring.
• Balance near-term delivery, including legacy migration, with longer-term capability and innovation.
• Work with the wider group data community to align UK plans with global standards, platforms and shared services where sensible.
• Delivery: own end-to-end delivery of data products that support the data and analytics strategy.
• Plan, prioritize and run projects across several business areas.
• Set delivery frameworks and standards for consistent quality and speed.
• Build clear timelines, track progress, and deal with risks and delays early.
• Document and present the value each data product delivers.
• Lead the move from legacy platforms such as Cognos, Oracle and Qlik to cloud platforms (Azure, Databricks and Power BI), including decommissioning plans and business continuity.
• Strengthen data quality through proactive monitoring, clear ownership, measurable standards, and efficient root-cause analysis and correction to prevent repeat issues.
• Business value: link every initiative to strategic priorities and measurable outcomes such as customer service, efficiency, revenue, margin, risk reduction and colleague productivity.
• Agree success measures, baselines, benefit targets and owners with business leaders before delivery starts.
• Embed data products and insights into business processes and decisions, driving adoption and the behavior change needed to realize value.
• Report benefits openly through the delivery lifecycle, step in where adoption or value falls short, and agree corrective actions.
• Use results to refine priorities, scale what works and improve return on data and analytics investment.
• AI and innovation: run a practical AI strategy that finds where AI, machine learning and automation can improve data and analytics work.
• Build AI-enabled ways of working in the data function, such as automated quality monitoring, AI-assisted development and testing, generated metadata and documentation, and natural-language access to insight.
• Work with business areas to prioritize and deliver high-value AI use cases across pharmaceutical supply chain, commercial and operational activity, each with a clear business case.
• Ensure AI is used responsibly, with controls for ethics, transparency, security, regulatory compliance and human oversight, working with Legal, Compliance, Information Security and global colleagues.
• Build AI skills and confidence in the team and wider business, and assess new tools and vendors.
• Governance and compliance: assess current governance maturity and lead a phased, pragmatic improvement plan with defined targets and progress reporting.
• Establish the core framework: policies and standards, ownership and stewardship, catalogue and lineage, quality rules and monitoring, master and reference data, and access controls.
• Make sure all data initiatives meet organizational governance frameworks, regulatory standards and the demands of a regulated healthcare and pharmaceutical distribution business.
• Work with Compliance, Legal, Information Security and Privacy to keep data secure, private and high quality.
• Set up governance processes covering documentation, auditing and reporting, and chair or facilitate the forums needed to sustain them.
• Build data accountability by making governance practical, proportionate and part of delivery rather than a separate control.
• Finance and commercial: manage the delivery budget for operating and capital spend, including forecasting, variance analysis and clear financial reporting to senior leaders.
• Build and defend business cases, directing investment to the initiatives with the greatest return and strategic value.
• Plan resources and headcount to match the roadmap, and make evidence-based recommendations when demand exceeds capacity.
• Monitor cloud data infrastructure for usage, capacity, performance and cost, to control spend and maximize benefits to Alliance Healthcare UK.
• Stakeholders: build strong relationships with business leaders so their data needs are prioritized and met.
• Be the main point of contact for stakeholders, balancing competing demands and managing expectations.
• Explain complex technical topics, including AI and governance, in plain business language.
• Negotiate timelines, resources and deliverables to keep the organization aligned.
• Turn complex delivery problems into clear business stories and lead steering committees, governance forums and executive reporting.
• Lead data fluency and data culture initiatives that build confidence in using data and AI across the business.
• Team: lead, coach and develop data professionals to produce high-quality solutions.
• Build a culture of accountability, collaboration, inclusion and continuous improvement.
• Identify capability gaps and build data delivery, governance and AI skills through hiring, development and partnerships.
• Support team wellbeing and resilience through significant change and pressure.

Requirements

• Significant senior experience leading data, analytics or technology delivery in large, complex organizations.
• Proven experience managing and being accountable for a significant budget, including forecasting, business cases and cost control.
• Proven experience developing and communicating a strategic data or technology roadmap that was successfully delivered.
• Proven experience leading and developing cross-functional teams and managing senior stakeholders.
• Excellent communication, presentation and reporting skills, with the ability to engage technical and non-technical audiences.
• Deep understanding of data platforms, governance and analytics solutions and how they serve the business, including experience improving governance in a low-maturity setting.
• Practical knowledge of how AI and machine learning can improve data and analytics processes, and of the governance and risk issues they raise.
• Experience leading change and delivering in fast-moving, high-pressure settings, ideally including cloud migration or legacy platform modernization.
• Knowledge of programme or portfolio methods such as Agile, SAFe, Prince2 or equivalent.
• A recognized data, governance or programme management qualification, or experience maturing data governance capabilities.
• Leadership presence and credibility that inspire teams to high performance.
• A clear, future-focused vision, and the discipline to turn it into delivery plans.
• Trust-building with stakeholders at every level, listening well, communicating persuasively and diplomatically, and handling hard conversations with empathy and candor.
• Rigorous budget planning, control and forecasting, with sound investment decisions and proven value for money.
• A track record of delivering complex programmes on time, within budget and to scope.
• Curiosity about emerging technology, with the judgement to separate real opportunity from hype and apply AI responsibly.
• A governance mindset that gets the business to adopt good data practice without slowing delivery.
• Ability to guide people through transformation with resilience and clarity, and to work across IT, the business, global teams and external suppliers.
• Calm, flexible focus on outcomes under pressure, and sound problem solving with incomplete information.
• Desirable: experience in change management in healthcare, pharmaceuticals, supply chain or other regulated industries.
• Desirable: hands-on familiarity with Azure, Databricks and Power BI, and with governance tools such as catalogue, lineage and data quality platforms.
• Desirable: experience with FinOps or cloud cost management.

Conditions

Full-time role.

Hybrid working.

Benefit offerings outside the US vary by country and follow local market practice.

Benefits

• Benefit offerings outside the US vary by country and follow local market practice, and eligibility and effective dates may differ, including for team members covered by collective bargaining agreements.