Job Description

Job Title: Digital Associate Director (Data Engineer)

Career Level: E

Introduction to role:

Are you ready to build the data backbone of a next‑generation, digitally enabled manufacturing site? In this role, you will turn strategic priorities into scalable, data‑driven solutions that strengthen real-time decision making and operational excellence across Production, Quality, Engineering and Supply Chain. Your work will enable connected, predictive and adaptive operations that ultimately help us deliver medicines to patients with greater reliability and speed.

Reporting to the Digital Lead and working closely with multi-functional collaborators, you will operate at the intersection of strategy and execution—translating business needs into robust data architectures, pipelines and analytics applications. Can you see yourself designing trusted data foundations, powering digital twins and AI use cases, and driving measurable improvements in compliance, performance and productivity in a regulated environment?

Accountabilities:

Digital Roadmap Delivery: Partner with site and enterprise collaborators to implement the digital roadmap for Singapore Operations, aligning initiatives to business priorities, operational needs and standards to deliver measurable value.

Program and Project Delivery: Lead and coordinate digital projects and workstreams with clear scope, landmarks and risk management; drive disciplined delivery that meets business case outcomes in a GMP context.

End‑to‑End Digital Integration: Define process requirements, user needs, data flows and integration points across platforms and analytics environments to connect systems and enable multi-functional insights.

Data Architecture and Pipelines: Design, develop and maintain site‑level data architectures and scalable pipelines that support manufacturing, quality, engineering and supply chain processes, improving availability, quality and accessibility of data.

Trusted Data Foundations: Establish and sustain data standards, metadata, governance practices and documentation that underpin reliable reporting, analytics and digital product deployment; ensure data is structured for reuse, scalability and compliance.

Analytics and AI Enablement: Partner with data scientists, engineers and business teams to prepare data and implementation support for dashboards, predictive analytics, AI‑enabled solutions and operational insights that improve performance, reliability and quality.

Performance and Adoption: Track delivery progress and post‑implementation outcomes; capture lessons learned, drive user adoption, and iterate to maximise impact and sustainability.

Governance and Prioritisation: Prepare updates for governance forums, highlight risks and dependencies, and support value‑ and feasibility‑based prioritisation decisions.

Digital Capability Building: Develop digital literacy and adoption through training coordination, user engagement and practical guidance on new systems, data products and ways of working.

Innovation and Continuous Improvement: Identify and deliver improvements to processes, data flows, reporting and tools—balancing innovation with GMP compliance, maintainability and real‑world practicality.

Digital Applications for Process Optimisation: Build applications such as digital twins or AI agents that enhance organisational efficiency and unlock new ways of working.

External and Internal Networks: Engage with internal digital communities and selected external partners or suppliers to share findings, align with standards and adopt relevant protocols.

Essential Skills/Experience:

Education:

• Bachelor’s or Master’s degree or equivalent experience in Engineering, Computer Science, Information Systems, Data Engineering, Business, or a related field

Experience:

• 5+ years in digital transformation, data engineering, analytics, or related roles.
• Proven track record delivering digital solutions or Industry 4.0 initiatives in manufacturing (preferably pharma/biologics)
• Experience in data engineering, building and maintaining robust data foundations and delivering scalable data pipelines, integrations, and data products that enable analytics, AI, and digital twin use cases across complex enterprise environments.
• Ability to lead cross-functional change in highly regulated environments
• Proven track record of leading complex, high-impact data science initiatives end-to-end, delivering measurable business or operational outcomes

Technical Skills:

• Knowledge of digital technologies (IoT, cloud platforms, AI/ML, data analytics, automation)
• Knowledge of data architecture principles and modern data platform design to enable real-time decision-making, trusted data flows, and closed-loop control across complex enterprise environments

Leadership Skills:

• Strong communicator with the ability to influence and collaborate effectively across cross-functional and matrix teams
• Demonstrated ability to operate at both strategic and operational levels, supporting delivery plans, managing risks, and ensuring effective execution
• Sound judgment and comfortable operating in a challenging, fast-paced and sometimes ambiguous environment
• Innovative, with strong focus and proven experience in delivering continuous improvement using digital solutions

Desirable Skills/Experience:

• Formal certification in relevant discipline
• Practical usage of Agile Methodology
• Experience of working in a global organisation with complex/geographical context
• Pharmaceutical business awareness/business domain knowledge
• Cross industry business awareness/business domain knowledge
• General understanding of manufacturing data systems (e.g. historian data, process monitoring platforms or integrated data environments)
• Previous expertise in one or more data science domains (e.g. multivariate analysis, statistical modelling, data visualization, workflow automation), with the ability to work across domains
• Experience performing data analysis, data profiling, and business-to-data translation.

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Why AstraZeneca:

Here, your engineering will power real outcomes for patients as we scale a modern, data‑led enterprise. We bring together unexpected combinations of expertise—manufacturing, analytics, automation, AI and machine learning—to spark bold ideas and turn them into production‑grade solutions. With strong backing and established platforms, you will experiment, learn fast and deliver at scale in a supportive, collaborative environment that values kindness alongside ambition. You will help define sustainable technologies, make data transparent and usable across the business, and see your work accelerate how medicines are made and delivered.

Call to Action:

If you are ready to architect the data foundations of a pioneering manufacturing site and turn ideas into measurable impact for patients and colleagues, step forward and help us build what comes next.

Date Posted

03-Aug-2026

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.