Job Title: Data Governance Specialist
Job Title: Data Governance Specialist
GCL : D2
Introduction to role:
Are you ready to turn complex, fast-moving data into trusted, governed assets that power automation and AI at scale for real impact on patients? This role places you at the heart of how we build reliable data foundations, accelerate decision-making, and drive efficiency across our manufacturing and supply network.
As the Data Governance Specialist, you will shape the standards, guardrails, and practices that make advanced analytics and AI solutions safe, transparent, and effective. You will work side by side with data quality experts and business leaders to translate priorities into governed data elements ensuring AI capabilities which will facilitate delivery of measurable business outcomes. Could you turn ambiguity into repeatable, high-quality data and services that reduce cycle time, increase right-first-time performance, and unlock new insights?
Accountabilities:
- Governance Product Roadmap: Deliver and maintain a prioritized roadmap that aligns governance policies, data standards, and automation/AI use cases with business objectives and technical feasibility.
- Data and Integration Specifications: Work directly with APIs, data models, and integrations to define specifications that ensure accuracy, interoperability, and traceability.
- Agile Ways of Working: Lead planning, refinement, reviews, and demos; ensure estimates are realistic and outcomes are measurable.
- Release Stewardship: Own go/no-go decisions, coordinate deployments, and validate releases against functional and non-functional requirements, including performance and security.
- Blocker Removal: Identify and escalate risks associated with technical and organizational impediments that slow delivery or compromise governance.
- For quality, compliance, and ethics, define and enforce non-functional requirements. Align with security policies, privacy regulations, and responsible AI principles. Strategically manage technical debt. Keep documentation and deployment status tools up to date.
- Metrics and Continuous Improvement: Establish targets for adoption, data quality, and operational health; drive experimentation and incremental enhancements; evaluate emerging tools and practices to keep our approach current and effective.
Essential Skills/Experience:
Education & Experience
- Bachelor's degree in Business, Data, Computer Science; an advanced degree or relevant equivalent experience is considered a plus.
- 7+ years in Operations/manufacturing data environments with 3+ years in a product ownership, technical delivery, or data science role.
- Proven track record of owning the full lifecycle of intelligent automation and machine learning solutions — from ideation and prototyping through product-ionization, deployment, and continuous improvement.
Technical Expertise
- Experience with data governance frameworks, data quality management, and data lifecycle controls.
- AI & Machine Learning: Solid understanding of machine learning algorithms, data pre-processing techniques, LLMs, and Generative AI — with the ability to assess feasibility, guide implementation, and validate outcomes.
- Automation & Integration: Hands-on experience with automation frameworks (RPA, intelligent automation, workflow orchestration) and integration patterns.
- Analytics & Computational Fluency: Proficiency with advanced analytics tools, software package deployment, and data structures to define detailed technical requirements and validate the work you're doing.
Product & Delivery Skills
- Backlog & Roadmap Management: Demonstrated ability to translate business problems into prioritized, sprint-ready user stories with clear acceptance criteria and measurable outcomes.
- Prototyping & Validation: Proactive, hands-on approach to building proof-of-concepts, running experiments, and applying design thinking to de-risk delivery.
- Quality & Governance Attitude: Strong analytical thinking for assessing solution performance and enforcing non-functional requirements.
Business & Stake-holder Engagement
- Storytelling & Communication: Excellent ability to craft compelling narratives around data, insights, and product value — combining creativity, pragmatism, and out-of-the-box thinking to influence senior leadership and multi-functional partners.
- Actionable Impact: Demonstrated ability to provide insights and automation solutions that generate quantifiable business value and operational efficiency gains.
- The stake-holder Translation: Skilled at bridging business needs and technical execution, eliciting requirements through qualitative and quantitative methods, and maintaining continuous feedback loops.
Attitude & Approach
- Proactive & Hands-On: Can-do attitude with a bias toward action — comfortable rolling up sleeves to prototype, test, solve, and validate alongside the team.
- Continuous Improvement: Passion for technology scouting, experimentation, and iterative learning to keep solutions current and high-performing.
- Ethical & Compliant: Commitment to responsible AI development, data governance, security standards, and regulatory compliance.
Desirable Skills/Experience:
- Hands-on use of data cataloging and lineage tools, and master data management practices.
- Background in pharmaceutical or regulated manufacturing environments, including familiarity with GxP.
- Knowledge of privacy and data protection regulations and model risk management for AI/ML.
- Experience with cloud data platforms and modern data engineering patterns.
- Certification or training in Lean, Six Sigma, or similar continuous improvement methodologies.
Here, your craft in data and governance fuels a mission with real-world consequences: reliable, timely delivery of life-changing medicines. You will work with a diverse, distributed team that brings scientists, engineers, and supply experts into the same room to spark bold ideas and faster execution. We keep pushing the boundary of what’s possible by pairing innovative technology with rigorous standards, and we value kindness alongside ambition. Expect a dynamic environment with new products and launches, where you can influence how modern data and AI practices scale across an end-to-end supply network. We collaborate in person several days a week to build momentum and learn from each other, while balancing flexibility to support how you do your best work.
Call to Action:
Join us to build trusted data foundations for automation and AI that accelerate how medicines reach patients—make your move today.
Date Posted
08-Jul-2026
Closing Date
28-Jul-2026
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.
