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Senior Director – EUIT Data & AI Forward Engineering Lead
AstraZeneca. Define and deliver the EUIT Data & AI Forward Engineering strategy .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in leading data and AI initiatives, developing technology teams, and implementing product-centric operating models. Proficient in establishing governance, security, and responsible AI practices while driving measurable business outcomes through technology investments.
Highest-signal resume keywords
Leadership Experience In Data And AIExperience With Generative AI And AutomationKnowledge Of Modern Cloud Data PlatformsAbility To Build Business CasesExperience Leading Geographically Distributed Teams
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Data EngineeringAI Capabilities DevelopmentAdvanced AnalyticsMachine LearningData GovernanceCloud EconomicsProduct-Centric Operating ModelsAutomationData ProductsDigital Transformation
Soft Skills
Building Trusted PartnershipsTeam DevelopmentCollaboration With Senior LeadersLeadership In Technology TransformationCommunication
Tools & Technologies
SnowflakeAI PlatformsCloud Data PlatformsAutomation ToolsData Analytics Tools
Industry Keywords
Data EcosystemsAI EcosystemsFinOpsPrivacySecurityRisk ManagementOperational PerformanceStrategic PartnershipsManaged ServicesTechnology Communities
Tech Stack
Tools & technologiesCloud
About the role
Key responsibilities & impact- Define and deliver the EUIT Data & AI Forward Engineering strategy
- Connect technology investment to business priorities
- Identify opportunities where data, AI and automation can improve decisions, simplify work and create measurable value
- Build a forward engineering model with multidisciplinary teams working closely with business colleagues
- Develop trusted, reusable data products and AI capabilities
- Establish engineering, architecture, security, governance, privacy, responsible AI and data quality practices
- Shape how AI agents are developed, deployed, managed and improved across EUIT
- Establish approaches for ownership, human oversight, observability, evaluation and cost management
- Create ways for teams to experiment with new technology and scale valuable solutions
- Establish baselines and measures with Finance and business partners
- Develop AI learning opportunities including hackathons, demonstrations, speaker sessions, communities of practice and role-based learning
- Build and develop a diverse team of forward engineers, data product leaders, AI specialists and technology leaders
- Evolve EUIT toward persistent, product-focused teams accountable for outcomes, adoption and continuous improvement
- Shape future skills and career pathways across forward engineering, data products, AI and agent engineering, platform architecture and value management
- Strengthen operational performance, resilience, automation and cost effectiveness with strategic partners and managed service providers
- Promote commercial and FinOps practices across data, cloud and AI investment
- Collaborate with senior business and technology leaders across Finance, HR, GBS, Legal, Compliance, M&A and EUIT
- Develop talent in India and the UK
Requirements
What you’ll need- Significant leadership experience in data, analytics, AI, engineering or digital transformation
- Experience building and developing technology teams
- Experience leading enterprise Data & AI platforms, products or engineering capabilities
- Experience moving AI, automation or advanced analytics from experimentation into scaled business use
- Experience with generative AI, agentic AI or comparable intelligent automation
- Experience building trusted partnerships with senior business and technology leaders
- Experience leading technology or operating-model transformation
- Experience managing strategic technology partners or outsourced services
- Experience improving productivity and demonstrating measurable business outcomes from technology investment
- Experience leading geographically distributed teams and developing future leaders
- Understanding of modern data and AI ecosystems
- Knowledge of modern cloud data platforms and ecosystems, including technologies such as Snowflake
- Knowledge of data engineering, data products, analytics and governance
- Knowledge of generative AI, agentic AI, machine learning and automation
- Knowledge of responsible AI, privacy, security and risk management
- Knowledge of cloud economics and FinOps
- Knowledge of product-centric technology operating models
- Ability to build business cases and connect technology investment with measurable outcomes
- Bachelor's degree or equivalent experience in Computer Science, Engineering, Data Science, Information Technology or a related subject area would be valuable
- Experience across different industries can bring useful perspective
- External engagement with Data, AI, engineering or technology communities would be welcomed
Benefits
Comp & perks- Inclusive environment with opportunities to contribute, develop and succeed
- Reasonable accommodations throughout the recruitment process