Data Engineering Specialist

• Job Description / Capsule

  The Data Engineer & Business Intelligence Specialist is responsible for designing, developing, and implementing new data technologies and reporting solutions that enable business insights and drive scalable data sharing practices.

  Typical Accountabilities

• Create and maintain optimal data pipeline architecture.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our analytics product into an innovative industry leader.
• Assembling large, complex sets of data that meet non-functional and functional business requirements.
• Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using AWS and SQL technologies
• Work with data architectures such as the Medallion Architecture, organizing data across bronze, silver, and gold layers to ensure scalability, data quality, and optimal data transformations throughout the pipeline.
• Develop and maintain conceptual, logical, and physical data models to ensure alignment with business requirements and technical designs. Ensure these models facilitate efficient data storage, transformation, and querying processes while maintaining scalability and performance
• 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 implementation 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.
• Collaborate with analyst, engineers, and data scientist to deliver high quality data architecture and pipelines.
• 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.
• Innovate and test 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 activities and project estimates which contribute to the creation of business case and delivery plans.
• Contribute to the continued development of Data Engineering as a capability - training, tooling, ways of working, and operating model to optimise output and value.
• 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.
• 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.
• Design, develop, and maintain Power BI dashboards and reports, ensuring they are based on detailed technical designs. Automate reporting processes, making them scalable, user-friendly, and delivering accurate, actionable insights for business decision-making.
• Collaborate with stakeholders to translate business requirements into detailed technical designs for reporting solutions, continuously optimizing Power BI performance and adhering to BI best practices for ongoing improvement.
• Ensure adherence to data governance frameworks, establishing and enforcing policies that guarantee data accuracy, consistency, security, and compliance across all systems. This includes overseeing data quality management practices and collaborating with stakeholders to maintain high standards of data integrity.

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

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.