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 architecture, infrastructure as code, data cataloging, lineage, and automated data quality frameworks.
Experience supporting Tableau, Power BI, or similar reporting and visualization solutions.
Experience working in a global, matrixed organization and using Agile or SAFe practices.
Exposure to machine learning or AI data foundations and responsible data enablement.
How you work
You take ownership from architecture through production support and make sound decisions that balance delivery, reliability, security, and maintainability.
You work effectively across disciplines and time zones, listen to users, and make complex topics understandable.
You bring strong analytical and troubleshooting skills, adapt to changing priorities, and help teammates grow through collaboration and feedback.
APPLY NOW
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EQUAL OPPORTUNITY STATEMENT
Amgen is an Equal Opportunity employer and will consider you without regard to your race, colour, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.
We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.
