SAP Analytics Lead – Operations Analytics

Role Title : SAP Analytics Lead – Operations Analytics

We are one purpose-led global organisation. The enablers and innovators, ensuring that we can fulfil our mission to drive scientific progress and discover and develop life-changing medicines. We take pride in working close to the cause, opening the locks to save lives, ultimately making a substantial difference to the outside world.

AstraZeneca (AZ) is growing strongly. Our employees have a shared goal to help patients globally. They rely on our medicines and scientific progress. In this journey AZ must continue to work across borders and with partners and new colleagues in a fast and detailed way. The ambition, size and complexity of the organisation, coupled with the opportunities afforded by new technology, has owned the Board to approve a large-scale transformation programme – Axial.

The Axial Programme will be powered by S/4HANA a new ERP (Enterprise Resource Planning) system which will be implemented right across the organisation and will provide our business with standardised processes, enhanced financial management, common data and real time reporting, redefining the way we work through our entire supply chain - from bench to patient.

The new system will be used by more than 20,000 employees daily, is foundational to all AZ entities and is central to most core business processes. This is a once in a generation programme for AstraZeneca and will build our methods of operation globally for many years to come.

The Axial programme needs the best talent to work in it. Whether it’s the technical skills, business understanding or change leadership, we want to ensure we have the strongest team deployed throughout. We are aiming to deliver a best-in-class change programme that leaves all employees with a fuller understanding of their role in the end-to-end nature of our global company. This programme will provide AZ with a competitive edge, to the benefit of our employees, customers and patients.

What you’ll do

We are looking for Data & Analytics leader who can shape ways of working, set standards and build a community of business analysts and Analytics engineers.

We are building an SAP analytics design & delivery team. Each team will have business analyst and Engineers embedded in the team. The Lead for SAP Operation Analytics is responsible for the strategy, design, delivery, and governance of operations analytics on SAP platforms, enabling accurate, timely, and trusted insights for decision-making. This role leads all aspects of the end-to-end operations analytics landscape across S/4HANA, SAP Analytics Cloud (SAC), SAP Datasphere and potentially with future roadmap products, orchestrating data products, analytics solutions, and performance management capabilities. You will partner with Operations, Finance, IT, and various organizational groups to drive value realization from SAP investments and modernize the enterprise Operations analytics operating model.

• Strategy and roadmap: Define the multi-year roadmap for SAP operations analytics covering demand/supply planning, manufacturing performance, inventory, procurement, logistics, quality, and sustainability; align with company-wide data and digital strategies in line with Line of Business strategy.
• Product ownership: Establish and govern operations analytics products (e.g., OTIF, service level, forecast accuracy, capacity utilization, OEE, cycle time, inventory turns, PPV, supplier performance, NCR/quality metrics) with clear KPIs, data contracts, and lifecycle management.
• Platform leadership: Supervise building and operation of SAP analytics platforms (embedded analytics within S/4HANA/CDS, Datasphere/BW/4HANA, HANA views, SAC stories/apps/planning) ensuring scalability, reliability, and security.
• Supply chain planning analytics: Integrate and operationalize analytics from SAP and S&OP, enabling driver-based planning and what-if simulations in SAC.
• Manufacturing and shop-floor insights: Build analytics for production orders, confirmations, yield, scrap, OEE; connect to MES/MII, IoT/telemetry, and quality results (QM) where applicable.
• Logistics and warehouse analytics: Deliver KPIs and dashboards for EWM, TM, and distribution (dock-to-stock, pick accuracy, dwell time, transport cost, carrier performance).
• Procurement and supplier analytics: Integrate Ariba and S/4 procurement for spend, supplier risk, lead times, compliance, and savings tracking.
• Data governance and quality: Implement data standards, master data controls (materials, BOMs, routings, suppliers, locations), lineage, and certifications; harmonize semantic models for product, plant, storage location, batch, unit of measure.
• Integration and interoperability: Connect SAP and non-SAP sources (S/4HANA, IBP, EWM, TM, Ariba, MES/MII, LIMS/QM, IoT platforms) to enterprise data platforms (Azure/Snowflake/Databricks) and BI tools while maintaining E2E process integrity across Plan, Source, Make, Deliver, and Quality.
• Controls and compliance: Ensure SOX, GXP alignment, audit-ability, access reviews, and segregation of duties; lead model validations for regulated contexts.
• Performance and cost optimization: Support the team in Driving query/story tuning, memory and compute optimization, licensing/utilization management, and cost-to-serve visibility.
• Operating model and talent: Build and lead a high-performing team (analytics engineers, product owners, modelers) and establish agile delivery practices, SLAs, and L3 support.
• Bus matrix ownership: Define and maintain the enterprise bus matrix (subject areas, conformed dimensions, fact families, KPIs) across domains such as Customer, Product, Sales, Finance, Operations, Supply Chain, and HR; drive reuse of conformed dimensions and metric definitions.
• Domain architecture: Partner with domain owners to design canonical models and subject‑area blueprints; align data products to business capabilities and processes.
• Data product contracts: Define data product SLAs, schemas, lineage, ownership (RACI), and quality rules; implement observability and certification for enterprise consumption.
• Stakeholder engagement: Partner with IT, Enterprise Process Owner organization, GSC Ops, and business units; run steering committees, prioritize backlogs, and communicate outcomes to executives.
• Change management and adoption: Lead enablement, training, and adoption programs; create standards, playbooks, and reusable assets to scale analytics across operations.
• Innovation and continuous improvement: Evaluate new SAP/non-SAP capabilities and pilot sophisticated use cases such as AI-assisted demand forecasting, predictive maintenance, and inventory optimization.

Essential for the role

• Expertise in SAP Analytics Stack – SAP Analytics Cloud/Datasphere.
• Operations domain expertise: Understanding of planning (IBP/S&OP), manufacturing (PP/QM/MES/MII), procurement (MM/Ariba), logistics (EWM/TM), and end-to-end process flows; experience with KPIs such as OTIF, OEE, inventory turns, forecast accuracy, and cycle time.
• S/4HANA embedded analytics and CDS; operations modules (MM, PP, QM, EWM, TM).
• SAP Datasphere and SAP Analytics Cloud (SAC) for stories, analytics applications, and planning; scenario modelling and allocations.
• Integration via ODP/OData, SLT/SDI, and connectivity to large-scale data solutions such as Azure, Snowflake, and Databricks.
• Leadership and delivery: Proven track record setting strategy, handling budgets, leading multi-functional teams, and delivering large, multi-country SAP analytics programs. Ability to set and drive a vision.
• Ability to thrive in ambiguous, change & ground-breaking program environment.
• Governance and controls: Experience with SOX, GXP, access control, and audit readiness.
• Tools and methods: Agile product management, backlog prioritization, CI/CD for analytics transports, Git, and modern observability practices.

Desirable for the role

• SAP Analytics tools certifications.
• Background in regulated industries (e.g., life sciences) with GxP considerations and validated systems.
• Exposure to Operations AI/ML forecasting, driver-based planning accelerators, and ESG reporting integration.
• Knowledge of master data and reference data tools (SAP MDG, data cataloguing).
• Familiarity with data science, AI/ML concepts and use cases.

Why AstraZeneca?

At Astrazeneca we’re dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and ignite your ambitious spirit. There’s no better place to make a difference to medicine, patients and society. An inclusive culture that champions diversity and collaboration, and always committed to lifelong learning, growth and development. We’re on an exciting journey to pioneer the future of healthcare.

So, what’s next?

• Are you already imaging yourself joining the team? Good, because we can’t wait to hear from you.
• Are you ready to bring new insights and fresh thinking to the table? Brilliant! We have one seat available and hope it's yours
• If you’re curious to know more than we welcome your application no later than

Where can I find out more?

Our Social Media, Follow AstraZeneca on LinkedIn https://www.linkedin.com/company/1603/

Follow AstraZeneca on Facebook https://www.facebook.com/astrazenecacareers/

Follow AstraZeneca on Instagram https://www.instagram.com/astrazeneca_careers/?hl=en

Date Posted

17-Dec-2025

Closing Date

AstraZeneca embraces diversity and equality of opportunity.  We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.  We believe that the more inclusive we are, the better our work will be.  We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.  We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.