Data Engineering Specialist

Typical People Management Responsibility (direct/indirect reports)

• 0 The approximate number of people managed in total (all levels)
• Matrix Manager – (projects/dotted line)
• Manager of a team
• Grandfather (manager of a manager)

What is the global remit?

(how many countries will the role operate in?)

Operates in:

• Own country X
• Another country
• 2 or 3 countries at a minimum of 40% of the time
• 4 or more countries at a minimum of 40% of time
• Remit which covers all AstraZeneca countries

Education, Qualifications, and Experience

Essential

• Bachelor’s Degree in Computer Science or a related technical field, and 7+ years of relevant employment experience.
• 7+ years of work experience with ETL, Data Modelling, and Data Architecture
• Solid experience in data modeling (conceptual, logical, and physical), ensuring that data solutions are scalable, efficient, and aligned with business requirements.
• Experience working with layered data architectures such as the Medallion Architecture (bronze, silver, and gold layers) to ensure data quality and optimization of transformation processes.
• Expert-level skills in writing and optimizing SQL
• Experience operating data warehouses and data lakes
• Demonstrated experience in a data engineering role with practical examples in developing using modern data platforms to build, deploy, and maintain data applications. Demonstrate efficiency in handling data - tracking data lineage, ensuring data quality, and improving discoverability of data.
• Strong ability to understand business requirements and translate them into effective technical designs for reporting solutions.
• Experience with AWS cloud services: S3, Redshift, Glue, Athena, Lambda. Certification is a plus. Experience with Snaplogic and Airflow
• Experience with object-oriented/object function scripting languages: Python
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• Knowledge and experience in project management, applying Agile or similar methodologies to coordinate cross-functional teams and ensure timely, on-budget delivery of data solutions.
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets. Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Proficiency or demonstratable passion for learning, in data engineer techniques and testing methodologies
• Proficiency or demonstratable passion for learning, with data and application design patterns and processes
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment. Self-starter, comfortable with ambiguity and will enjoy working in a fast-paced dynamic environment.

Desirable

• Industry experience with data, in large, complex data settings, consultancy or vendor experience
• Experience with DevOps or DataOps concepts, preferable hands-on experience implementing continuous integration or highly automated end-to-end environments
• Power BI certification or equivalent experience with leading BI tools.
• Experience implementing a microservices architecture
• Proven experience of leading and growing engineering teams

• Experience in reusing of metadata and prebuilt components from cataloguing tools
• Experience implementing data governance frameworks to ensure data accuracy, consistency, security, and compliance with organizational and regulatory standards.
• Experience on ML/DL or any other data science technique
• 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

Key Relationships to reach solutions

Internal (to AZ or team)

• Working with Business Units, Bex and other IDs departments in the conceptualization of data products and capabilities.
• Working with peers, data architects, data sciencist and, data analysts in the delivery of data capabilities
• Working with PM/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

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.