Senior Data Engineer

Career Category Information Systems Job Description Join our team at AMGEN Capability Center Portugal, consistently recognized among the top companies in the Best Workplaces(TM) ranking by Great Place to Work(R) in Portugal. In 2026, we were once again distinguished as one of the top Best Workplaces in the country (category 201-500 employees), reinforcing our commitment to an exceptional employee experience and workplace culture. We are a team of over 500 talented individuals, spanning more than 30 functions and areas of expertise, and representing over 40 nationalities. Together, we bring diverse perspectives and professional backgrounds to help shape the future of healthcare through innovation and technology. This is your opportunity to explore a world of possibilities across areas such as Data & Analytics, Digital, Technology & Innovation, Cybersecurity, R&D Operations, Global Distribution, Finance, Regulatory Affairs, General & Administrative, Human Resources, and many more. Located in the heart of Lisbon, our AMGEN office foster a culture of innovation, excellence, and purpose. Come thrive with us at AMGEN, supporting our mission To Serve Patients. What we do at AMGEN matters in people's lives.

Senior Data Engineer Global Medical Data and Analytics Role Overview

Join Amgen’s Global Medical Data and Analytics organization and help build trusted data products that support better decisions for medical teams. As a Senior Data Engineer, you will lead the design and delivery of scalable data pipelines and lakehouse solutions while contributing to data architecture, modeling, integration, and operational standards. You will partner with product owners, architects, analytics teams, validation engineers, and business stakeholders to turn complex needs into secure, reliable, and reusable data capabilities.

What you will do

• Lead the design, development, testing, deployment, and support of robust batch and near-real-time data pipelines across source, landing, curated, and analytics layers.
• Design end-to-end data architecture for cloud-based lakehouse solutions, including data ingestion, transformation, storage, serving, and integration patterns.
• Build and optimize solutions on Databricks using Python, SQL, Spark, Delta Lake, and related platform capabilities; work with AWS cloud services and enterprise data lake technologies.
• Design data models and curated datasets for analytics and reporting, applying dimensional modeling and other appropriate modeling patterns while maintaining clear definitions and lineage.
• Develop and support API-based integrations and reusable ingestion frameworks that connect enterprise and business systems.
• Apply engineering practices for orchestration, configuration, CI/CD, automated testing, version control, deployment, and environment management.
• Own data quality, reconciliation, observability, performance, scalability, and cost efficiency; diagnose production issues and improve reliability.
• Build in privacy, access controls, retention, auditability, and regulatory expectations such as HIPAA and GDPR into data solutions in partnership with governance and security teams.
• Collaborate with product owners and cross-functional teams in an Agile/SAFe environment to shape requirements, estimate work, communicate trade-offs, and deliver iteratively.
• Provide technical guidance, conduct design and code reviews, document architectural decisions, and mentor engineers across the team.
• Enable downstream analytics and visualization, including Tableau or comparable BI tools, by delivering well-governed, performant, and documented data products.

Basic qualifications

• 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 data pipelines and analytical data platforms.
• Strong hands-on proficiency with Python and SQL, and experience with Apache Spark or a comparable distributed data processing framework.
• Experience with Databricks and cloud data platforms, preferably AWS, including lakehouse or data lake technologies.
• Experience with data modeling, ETL/ELT design, API or system integration, and workflow orchestration.
• Ability to communicate technical designs and data concepts clearly to technical and non-technical partners.

Preferred qualifications

• Experience in biotechnology, pharmaceuticals, healthcare, or another regulated industry.
• Familiarity with medical, field medical, medical information, or scientific communications data and processes.
• Experience with Delta Lake, cloud-native a