Senior Data Engineer - Global Medical Data & Analytics

About the role

AMGEN Capability Center Portugal, based in Lisbon, is hiring a Senior Data Engineer within its Global Medical Data and Analytics organization. The role leads the design and delivery of scalable data pipelines and lakehouse solutions, partnering with product owners, architects, analytics teams and business stakeholders to build secure, reliable and reusable data capabilities.

Key responsibilities

• Lead the design, development, testing, deployment and support of batch and near-real-time data pipelines across source, landing, curated and analytics layers.
• Design end-to-end cloud-based lakehouse architectures covering ingestion, transformation, storage, serving and integration.
• Build and optimize solutions on Databricks using Python, SQL, Spark, Delta Lake and AWS cloud services.
• Design data models and curated datasets for analytics and reporting, with clear definitions and lineage.
• Develop API-based integrations and reusable ingestion frameworks connecting enterprise and business systems.
• Apply engineering practices for orchestration, CI/CD, automated testing, version control and environment management.
• Own data quality, reconciliation, observability, performance, scalability and cost efficiency, and fix production issues.
• Incorporate privacy, access controls, retention, auditability and regulations such as HIPAA and GDPR with governance and security teams.
• Work in an Agile/SAFe environment, provide technical guidance, run design and code reviews, document architecture and mentor engineers.
• Enable downstream analytics and visualization with Tableau or comparable BI tools.

Required profile

• 9+ years of professional experience in data engineering, data platform engineering or a closely related field.
• Bachelor's degree in computer science, information systems, engineering or a related discipline, or equivalent practical experience.
• Demonstrated experience designing data architecture and delivering production-grade pipelines and analytical platforms.
• Ability to explain technical designs and data concepts to technical and non-technical partners.

Required skills

• Strong hands-on proficiency with Python and SQL.
• Apache Spark or a comparable distributed data processing framework.
• Databricks and cloud data platforms, preferably AWS, including lakehouse or data lake technologies.
• Data modeling, ETL/ELT design, API or system integration and workflow orchestration.
• Preferred: Delta Lake, cloud-native architecture, infrastructure as code, data cataloging, lineage, automated data quality, Tableau/Power BI, global matrixed organizations, Agile/SAFe, and machine learning/AI data foundations.