Explicitly requires vibe coding using large language models in production systems.
About the Role
Amgen is hiring a Data Engineer to design, develop, and maintain scalable data pipelines and platforms within an AI & Data Science product team. The role focuses on implementing ETL/ELT processes, ensuring data quality and system performance, and leveraging cloud and enterprise platforms like Databricks and AWS while working in a SAFE Agile environment.
Job Description
Role
As a Data Engineer in the AI & Data Science department, you will develop and implement data strategy, build and optimize data pipelines and platforms, and ensure availability and performance of critical systems. You will collaborate with product managers, designers, and engineers in a SAFE Agile product team and support enterprise resource management capabilities.
Key Responsibilities
- Design, develop, and implement data pipelines, ETL/ELT processes, and data integration solutions.
- Deliver data pipeline projects from development to deployment, managing timelines and risks.
- Ensure data quality and integrity through testing and monitoring.
- Leverage cloud platforms (e.g., AWS, Databricks) to build scalable data solutions.
- Automate operations, monitor system health, and respond to incidents to minimize downtime.
- Work closely with product teams and stakeholders to understand data requirements.
- Apply data engineering industry standards and best practices.
- Participate in Agile development, ceremonies, and collaborate with global teams.
Requirements
Basic Qualifications
- Bachelor’s degree in Computer Science, Information Technology, or related field.
- 5–9 years of relevant experience.
- Proficiency in at least one programming language (Python, Scala, or similar).
- Experience with data engineering platforms such as Databricks.
- Experience using large language models in production (vibe coding).
- Familiarity with cloud platforms and system integration.
- Ability to work effectively in teams and communicate clearly.
Functional Skills (Must-Have)
- Data modeling and structuring.
- ETL orchestration technologies and data integration.
- Software engineering best practices: version control (Git, Subversion), CI/CD (Jenkins, Maven), automated unit testing, DevOps.
- SQL and NoSQL databases.
- Experience in Agile/Scrum methodologies.
- Experience with version control and release management.
- Experience working with global teams.
Good-to-Have
- Familiarity with enterprise collaboration platforms: O365, SharePoint Online, MS Teams.
- Exposure to incorporating AI toolsets into development workflows.
- Experience in analytics or business intelligence roles.
- Certifications related to Databricks, Agile, or cloud platforms.
Soft Skills
- Strong analytical and troubleshooting skills.
- Comfortable working with global, virtual teams.
- Initiative, self-motivation, and eagerness to learn.
Team & Platforms
This role works with enterprise platforms including Databricks and MuleSoft and collaboration tools like O365, SharePoint Online, and MS Teams. The team follows SAFE Agile practices and emphasizes scalable, production-grade data engineering solutions.