Full Stack Data Engineer – Data Analytics and AI

Location: Hybrid (3 days on-site in Guadalajara, MX; 2 days remote)

About AstraZeneca

AstraZeneca is a global, science-led biopharmaceutical company focused on the discovery, development and commercialisation of life-changing medicines. Our Enterprise AI team delivers the AI app store, reusable AI models and ready-to-use ML platforms that power everything from early-stage drug discovery to patient-safety systems.

You will be joining the Data Analytics and AI (DA&AI) organization within Operations IT, responsible for delivering state-of-the-art Data Analytics and AI solutions for Operations capability areas like Pharmaceutical Technology Development, Manufacturing & Global Engineering, Quality Control, Sustainability, Supply Chain, Logistics and Global External Sourcing and Procurement. Here our work has a direct impact on patients – transforming our ability to develop life-changing medicines. We empower the business to perform at its peak and lead a new way of working, combining cutting-edge science with leading digital technology platforms and data.  

As a Full stack data engineer, you will Collaborate with a diverse team of UI/UX designers, architects, full-stack engineers, data engineers, and DevOps engineers to develop high-impact, scalable, and innovative products that deliver actionable insights and support our business goals.

Key Responsibilities:

• Develop, Maintain, and Optimize the scalable data pipelines for data integration, transformation, and analysis, ensuring high performance and reliability.
• Demonstrate proficiency in ETL/ELT processes, including writing, testing, and maintaining high-quality code for data ingestion and transformation. 
• Improve the efficiency and performance of data pipeline and workflows, utilizing advanced data engineering techniques and best practices.
• Develop and maintain data models that represent data structure and relationships, ensuring alignment with business requirements and enhancing data usability.
• Develop APIs and microservices for seamless data integration across platforms and collaborate with software engineers to integrate front-end and back-end components with data platform.
• Optimize and tune databases and queries for maximum performance and reliability and maintain existing data pipelines to improve performance and quality.
• Mentor other developers on best practices, conduct peer programming, code reviews, and help evolve systems architecture to consistently improve development efficiency.
• Ensure compliance with data security and privacy regulations and implement data validation and cleansing techniques to maintain consistency.
• Stay updated with emerging technologies, best practices in data engineering and software development, and contribute to all phases of the software development lifecycle (SDLC) processes.
• Work closely with data scientists, analysts, stakeholders, and product managers to understand requirements, deliver high-quality data solutions, and support alignment of data sources and specifications.
• Perform unit testing, system integration testing, regression testing, and assist with user acceptance testing to ensure data solutions meet quality standards. Work with the QA Team to develop testing protocols and identify and correct challenges.
• Maintain clear documentation for Knowledge Base Articles (KBAs), data models, pipeline documentation, and deployment release notes.
• Diagnose and resolve complex issues related to data pipelines, backend services, and frontend applications, ensuring smooth operation and user satisfaction.
• Utilize and manage cloud-based services (e.g., AWS) for data storage and processing, and implement and manage CI/CD pipelines, version control, and deployment processes.
• Liaise with internal teams and third-party vendors to address application issues and project needs effectively.
• Create and maintain data visualizations and dashboards to provide actionable insights.

Essential Skills:

• Minimum 7+ years of experience in developing and delivering software engineering and data engineering solutions.
• Extensive experience with ELT/ETL tools such as SnapLogic, FiveTran, or similar.
• Deep expertise in Snowflake, DBT (Data Build Tool), and similar data warehousing technologies.
• Proficient in designing and optimizing data models and transformations for large-scale data systems.
• Strong knowledge of data pipeline principles, including dimensional modelling, schema design, and data integration patterns.
• Familiarity with Data Mesh and Data Product concepts, including experience in delivering and managing data products.
• Strong data orchestration skills to effectively manage and streamline data workflows and processes.
• Proficiency in data visualization technologies, with experience in advanced use of tools such as Power BI or similar.
• Solid understanding of DevOps practices, including CI/CD pipelines, version control systems like GitHub. Ability to implement and maintain automated deployment and integration processes.
• Experience with containerization technologies like Docker and orchestration tools like Kubernetes.
• Automated testing frameworks (Unit Test, system integration testing, regression testing & data testing).
• Strong proficiency in programming languages such as Python, Java, or Similar. Experience with both relational (e.g., MySQL, PostgreSQL) and NoSQL databases.
• Deep technical expertise in building software and analytical solutions with modern JavaScript stack (Node.js, ReactJS, AngularJS).
• Strong knowledge of cloud-based data, compute, and storage services, including AWS (S3, EC2, RDS, EBS, Lambda), and orchestration services (e.g., Airflow, MWAA) and containerization services (e.g., ECS, EKS).
• Excellent communication and interpersonal skills, with a proven ability of managing stakeholder expectations, gathering requirements, and translating them into technical solutions.
• Experience workincomg in Agile development environments, with a strong understanding of Agile principles and practices. Ability to adapt to changing requirements and contribute to iterative development cycles.
• Advanced SQL skills for data analysis. Expertise on problem-solving skills with a focus on finding innovative solutions to complex data challenges.
• Strong analytical and reasoning skills, with the ability to visualize processes and outcomes. Strategic thinker with a focus on finding innovative solutions to complex data challenges and proactively addressing potential issues and bottlenecks.

Desired:

• Bachelor's or Master's degree in health sciences, Life Sciences, Data Management, Information Technology, or a related field, or equivalent experience.
• Significant experience working in the pharmaceuticals industry, with a deep understanding of industry-specific data requirements
• Demonstrated ability to manage and collaborate with a diverse range of stakeholders, ensuring high levels of satisfaction and successful project delivery.
• Proven capability to work independently and thrive in a dynamic, fast-paced environment, managing multiple tasks and adapting to evolving conditions.
• Experience working in large multinational organizations, especially within pharmaceutical or similar environments, demonstrating familiarity with global data systems and processes.
• Certification in AWS Cloud or other relevant data engineering or software engineering certifications, showcasing advanced knowledge and technical proficiency.
• 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.

ABOUT THE OPERATIONS IT TEAM

Operations IT is a global IT capability supporting the Global Operations organisation. We partner with Operations capability areas: Pharmaceutical Technology Development, Manufacturing & Global Engineering, Quality Control, Sustainability, Supply Chain, Logistics & Global External Sourcing & Procurement. Here our work has a direct impact on patients – redefining our ability to develop life-changing medicines. All with a passion to impact lives through data, analytics, AI, machine learning & more.

WHY JOIN US

Here our work has a direct impact on patients – transforming our ability to develop life-changing medicines. We empower the business to perform at its peak and lead a new way of working, combining innovative science with leading digital technology platforms and data. All with a passion to impact lives through data, analytics, AI, machine learning and more. Join us at a crucial stage of our journey in becoming a digital and data-led enterprise. Make the impossible possible by building partnerships and ecosystems, creating new ways of working and driving scale and speed to deliver exponential growth. Focused and committed, and backed with the investment to succeed, we are driving cross-company change to disrupt the entire industry.

ABOUT ASTRAZENECA

At AstraZeneca, we are dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and unleash your entrepreneurial spirit. There is no better place to make a difference to medicine, patients, and society. An inclusive culture that champions diversity and collaboration. Always committed to lifelong learning, growth, and development.

SO, WHAT NEXT?

If you are interested in applying, we encourage you to apply using your completed Workday profile where possible.

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.

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.