Digital Associate Director (Data Engineer)

Job Title: Digital Associate Director (Data Engineer)

Career Level: E

Introduction to role:

Are you ready to build the data backbone of a nextgeneration digitally enabled manufacturing site In this role you will turn strategic priorities into scalable datadriven 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 executiontranslating 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.

EndtoEnd 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 sitelevel 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 AIenabled solutions and operational insights that improve performance reliability and quality.

Performance and Adoption: Track delivery progress and postimplementation 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 feasibilitybased 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 toolsbalancing innovation with GMP compliance maintainability and realworld 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:

• Bachelors or Masters 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 -person working gives us the platform we need to connect work at pace and challenge perceptions. Thats why we work on average a minimum of three days per week from the office. But that doesnt mean were 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 dataled enterprise. We bring together unexpected combinations of expertisemanufacturing analytics automation AI and machine learningto spark bold ideas and turn them into productiongrade 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

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.