Data Engineer
Join our Operations IT team, a global IT capability supporting the Global Operations organization. We partner with various Operations capability areas such as Pharmaceutical Technology Development, Manufacturing & Global Engineering, Quality Control, Sustainability, Supply Chain, Logistics & Global External Sourcing & Procurement. Our work directly impacts patients by redefining our ability to develop life-changing medicines. We are passionate about impacting lives through data, analytics, AI, machine learning, and more.
As part of the Data Analytics and AI (DA&AI) organization within Operations IT, you will deliver brand-new Data Analytics and AI solutions for various Operations capability areas. Our work transforms our ability to develop life-changing medicines, empowering the business to perform at its peak. We combine powerful science with leading digital technology platforms and data.
As a Data Engineer, you will be responsible for building and maintaining scalable, high-performance data solutions that enable data-driven decision-making. Your primary focus will be on data ingestion, transformation, and orchestration across cloud-based platforms. In addition to core data engineering responsibilities, you will also collaborate on cloud architecture and contribute to software engineering efforts to support the end-to-end delivery of data products. You’ll work closely with cross-functional teams—including Data Engineering, Cloud Engineering, and Software Development—to ensure seamless integration, performance, and reliability of data pipelines and services.
Accountabilities
Build and optimize scalable data pipelines for ingestion, transformation, and analysis to ensure performance and reliability.
Develop and maintain efficient ETL/ELT processes using clean, testable, and production-ready code.
Design and manage data models that align with business requirements and support analytical use cases.
Collaborate with cross-functional teams (software engineers, data scientists, product managers) to deliver integrated data solutions.
Implement and manage cloud-based data infrastructure, leveraging services like AWS for storage, processing, and orchestration.
Create APIs and microservices to enable seamless data integration across platforms and systems.
Optimize databases and queries for performance and maintain high-quality, reliable data workflows.
Ensure data quality, validation, and compliance with security and privacy standards.
Document data pipelines, models, and processes for maintainability and knowledge sharing.
Stay up to date with modern data engineering tools and practices, contributing to ongoing improvements in architecture and delivery.
Essential Skills/Experience
Minimum 6+ years of experience in delivering data and software engineering solutions.
Hands-on experience with ETL/ELT tools like SnapLogic, FiveTran, or similar.
Strong expertise in Snowflake, DBT, and modern data warehouse technologies.
Skilled in data modelling, data transformation, and handling large-scale data systems.
Good understanding of data pipeline design, including dimensional modelling and schema development.
Familiar with Data Mesh and Data Product concepts, with experience in managing reusable data assets.
Experience with data orchestration tools like Apache Airflow or MWAA.
Proficient in Power BI or similar tools for building dashboards and data visualizations.
Knowledge of DevOps/DataOps, including CI/CD pipelines and GitHub for version control.
Familiar with Docker and Kubernetes for containerization and deployment.
Experience with automated testing for data (unit, integration, regression testing).
Strong programming skills in Python or similar languages.
Experience with SQL and both relational (MySQL, PostgreSQL) and NoSQL databases.
Exposure to full-stack development using JavaScript frameworks (Node.js, ReactJS, Python Fast API).
Solid experience working with AWS services (S3, EC2, RDS, Lambda, EKS, ECS).
Strong communication skills and ability to work closely with stakeholders to translate requirements into solutions.
Comfortable working in Agile environments, with the ability to adapt quickly to change.
Excellent problem-solving and analytical thinking, with a proactive approach to identifying and resolving issues.
Desirable Skills/Experience
Bachelor's or master's degree in a relevant field such as Health Sciences, Life Sciences, Data Management, Information Technology or equivalent experience.
Experience working in the pharmaceuticals industry
Certification in AWS Cloud or any data engineering or software engineering-related certification
Awareness of use case specific GenAI tools available in the market and their application in day-to-day work scenarios.
Possess working knowledge of basic prompting techniques and continuously improve these skills.
Stay up to date with developments in AI and GenAI, applying new insights to work-related situations
Awareness of use case specific GenAI tools available in the market and their application in day-to-day work scenarios.
Possess working knowledge of basic prompting techniques and continuously improve these skills.
Stay up to date with developments in AI and GenAI, applying new insights to work-related situations
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 authorisation and employment eligibility verification requirements.
