PRINCIPAL PRODUCT LEAD – DATA ANALYTICS AND AI

Typical Accountabilities.
• Provides management to their team of engineers to ensure successful delivery of teams' objectives.
• Provide data and analytics solutions either through enterprise services or direct to AstraZeneca functions.
• Deliver robust, cost-effective, automated solutions to support frequently asked business questions/analytical demands.
• Responsible for the development of engineering standards, roadmaps and blueprints that maximises current technology platforms and adapts to new data technology, working closely with Data Architects and Solution Architects.
• Test and quality assess new data and analytics and DataOps solutions, to ensure they are fit for release.
code assurance, Unit and System Integration Testing performance tuning, data testing, release management control and support of production processes including their SLAs.
• Oversee and manage the work of other Data Engineers, on and offshore, ensuring the quality of the delivery, guiding in best practice, problem-solving design/delivery challenges.
• Lead innovation and testing of new technologies with relevance to data and analytics, including proof of technology/value assessments and business case development.
• Responsible for data and analytics solution evaluation and selection decisions; buy vs build decisions, and project estimates which contribute to the creation of business case and delivery plans.
• Lead the contribution to the continued development of Data Engineering as a capability - training, tooling, ways of working, and operating model to optimise output and value.
• May manage the relationship with key suppliers (technology and Engineering service providers).
• Ensure that business data and information assets are made available as data services and artefacts for consumption by the wider AstraZeneca enterprise to ensure consistency and strategic alignment of all data and business intelligence solutions.
• Establish strong working relationships with AstraZeneca data and analytics stakeholder groups to develop an in-depth understanding of business priorities and early insight into changing needs in order to inform and shape demand.
• Selection and implementation of data management technologies and industry best practices, in alignment with the Enterprise Architecture and Technology Innovation functions.
• Maintain an on-going professional development in data and analytics technologies (and methodologies) to keep AstraZeneca current with advancing and changing data technology landscape and innovation.
• Development and delivery of data management and business intelligence practices and technology training programmes – (i.
.
AstraZeneca Data Engineering University).
Typical People Management Responsibility (direct / indirect reports).
• Approximate number of people managed in total (all levels) - None • Manager of a team • Matrix Manager – (projects/dotted line) What is the global remit? (how many countries will the role operate in?).
Education, Qualifications, Skills and Experience.
• Essential.
Bachelors Degree or equivalent number of years of experience in a Computer Science or Data Management related field; Significant years of experience in a data engineering role with practical examples in developing using modern data platforms to build, deploy, and maintain data applications; The role holder will possess a blend of design skills needed for Agile data development projects; Proficiency in data engineer techniques and testing methodologies; Proficiency in data development technologies; Proficiency with data and application design patterns and processes • Desirable.
Masters in Computer Science and Data Management or suitable experience; Experience with DevOps or DataOps concepts, preferable hands-on experience implementing continuous integration or highly automated end-to-end environments; Experience implementing a microservices architecture; Proven experience of leading and growing engineering teams; Industry experience with data in large, complex data settings, consultancy or vendor experience; Experience in reusing of metadata and prebuilt components from cataloguing tools; Good commercial awareness and understanding of the external market for data-related technology and best practices; Demonstrate initiative, strong customer orientation, and cross-cultural working; Exposure to Data Pipelines (Ingest & Store, Data Preparation, Discover & Present, Insight & Experience) Key Relationship to reach solutions.
• Internal (to AZ or team).
Working with peers, data architects, and, data analysts in the delivery of data capabilities; Working with Scrum leaders in daily updates on delivery estimations and issues management; Other data engineers in AZ in a Data Engineering Community that extend data engineering approaches and best practices • External (to AZ).
Outsource partners to deliver and support data structures and data provisioning processes 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.