Lead AI & Data Engineer – APD Platform
AstraZeneca21 hours ago
Barcelona, SpainStaff+
Responsibilities
- Design, develop, test, deploy, and maintain production-quality data and AI engineering solutions for the APD Platform.
- Build data pipelines, data products, analytical services, machine learning capabilities, and AI-enabled applications.
- Prepare, integrate, transform, and manage structured and unstructured data while implementing quality, validation, lineage, metadata, access control, and governance measures.
- Contribute to AI and machine learning operationalization, including model deployment, monitoring, evaluation, versioning, and lifecycle management.
- Contribute to platform architecture, reusable engineering patterns, technical standards, documentation, peer reviews, and continuous improvement.
- Apply DevOps practices including automated testing, infrastructure as code, containerization, monitoring, alerting, and incident resolution.
- Provide technical direction, guide architecture and solution design, mentor engineers, facilitate technical discussions, and influence cross-functional stakeholders.
Requirements
- Substantial experience in data engineering, AI engineering, software engineering, or a closely related discipline, with technical leadership experience delivering production-quality enterprise solutions.
- Strong programming experience in Python and/or another modern programming language, plus knowledge of SQL, data modeling, APIs, version control, automated testing, and software development practices.
- Experience designing and implementing data pipelines, data products, or data platforms using cloud technologies.
- Familiarity with major cloud platforms and services for storage, compute, databases, analytics, machine learning, identity, and monitoring.
- Understanding of machine learning engineering and MLOps principles, including model workflows, deployment, monitoring, reproducibility, performance evaluation, and lifecycle management.
- Experience with AI/ML solutions, generative AI applications, LLM integration, retrieval-augmented generation, model evaluation, or AI service deployment is valuable.
- Comfort with CI/CD, infrastructure as code, containerization, observability, and agile delivery; experience with Spark, Docker, Kubernetes, Terraform, or Git-based workflows is beneficial.
- Strong communication, collaboration, structured problem-solving, stakeholder engagement, and cross-disciplinary teamwork skills.
- Experience in pharmaceutical, biotechnology, healthcare, life sciences, regulated technology, scientific data, data governance, privacy, information security, FAIR data, responsible AI, knowledge graphs, semantic data models, or scientific computing is desirable.
- A degree or equivalent professional experience in computer science, engineering, data science, mathematics, life sciences, or a related subject is preferred.
- Experience with PowerBI, Startburst, Snowflake, AWS Glue, Terraform, LangChain, LangGraph, LangSmith, FastAPI, Pydantic, or Pandas is desirable.
Benefits
- In-person working averages a minimum of three days per week in the office, with flexibility around individual circumstances.
- Opportunity to work on meaningful technical and scientific challenges supporting medicine discovery and development worldwide.
- Inclusive environment with opportunities to collaborate across disciplines, develop, and contribute to life-changing medicines.
Tech Stack
Categories
Data EngineeringML Engineering
About AstraZeneca
AstraZeneca is a global biopharmaceutical company that discovers, develops, manufactures, and commercializes prescription medicines for patients and healthcare systems. Its portfolio spans oncology, cardiovascular, renal and metabolism, respiratory and immunology, and rare diseases (expanded by the 2021 acquisition of Alexion). Founded in 1999 and headquartered in Cambridge, UK, it is a public company listed on the London Stock Exchange and Nasdaq, generating revenue primarily from drug sales and partnerships.