About the Role
The role is responsible for developing and maintaining the data architecture across data analytics platforms and applications, along with liaising with the architecture team that includes activities required for data flow design, data modelling, physical data design, and query performance optimization.
The Data Modeler architect position is responsible for developing business information models by studying the business, our data, and the industry. This role involves creating data models to realize a connected data ecosystem that empowers consumers, drives cross‑functional data interoperability, enables efficient decision‑making, and supports AI usage of foundational data.
Roles & Responsibilities
- Develop and maintain conceptual, logical, and physical data models to support business needs.
- Contribute to and enforce data standards, governance policies, and best practices.
- Design and manage metadata structures to enhance information retrieval and usability.
- Maintain comprehensive documentation of the architecture, including principles, standards, and models.
- Evaluate and recommend technologies and tools that best fit the solution requirements.
- Drive continuous improvement in the architecture by identifying opportunities for innovation and efficiency.
Basic Qualifications and Experience
- Doctorate degree.
- Master’s degree with 4‑6 years of experience in Computer Science, IT, or a related field.
- Bachelor’s degree with 6‑8 years of experience in Computer Science, IT, or a related field.
- Diploma with 10‑12 years of experience in Computer Science, IT, or a related field.
Functional Skills
Must‑Have Skills
- Data modeling: proficiency in creating conceptual, logical, and physical data models.
- Ability to interview and communicate with business subject‑matter experts to develop data models that are useful for their analysis needs.
- Metadata management: knowledge of metadata standards, taxonomies, and ontologies to ensure data consistency and quality.
- Hands‑on experience with big‑data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), and performance tuning of big‑data processing.
- Implementing data testing and data quality strategies.
Good‑to‑Have Skills
- Experience with graph technologies such as Stardog, AllegroGraph, MarkLogic.
Professional Certifications
- Certifications in Databricks are desired.
Soft Skills
- Excellent critical‑thinking and problem‑solving skills.
- Strong communication and collaboration skills.
- Demonstrated awareness of how to function in a team setting.
- Demonstrated awareness of presentation skills.
EQUAL OPPORTUNITY STATEMENT
Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. 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.