Senior Data Architect & Platform Leader

Amgen; Thousand Oaks (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Amgen in Thousand Oaks, CA seeks a Principal Data Engineer to lead the design, development, and implementation of our data strategy. You will architect robust data platforms, mentor a team of data engineers, and collaborate with business stakeholders to translate data needs into scalable solutions.

The role requires deep knowledge of cloud architectures (AWS/Azure/GCP), Python, PySpark, SQL, and experience building data pipelines.

Qualifications

• Doctorate or Master's with data engineering experience.
• Bachelor's degree with 6+ years data engineering experience.
• Associate's degree with 10 years data engineering experience.
• High school diploma with 12 years data engineering experience.
• AWS Data Engineer certification preferred.
• Databricks Certificate preferred.

Responsibilities

• Lead design, development, and implementation of the data strategy.
• Architect and oversee robust data platforms and pipelines.
• Mentor and guide a team of data engineers.
• Oversee data governance, quality, security and compliance.
• Collaborate with stakeholders to translate data requirements into solutions.
• Stay abreast of emerging data technologies and opportunities.

Skills

Cloud platforms

Python / PySpark

SQL

Leadership

Problem solving

Education

Doctorate + 2 years data eng

Master's + 4 years data eng

Bachelor's + 6 years data eng

Associate + 10 years data eng

High school diploma + 12 years data eng

Tools

Apache Spark

Apache Airflow

Git / SVN / CI/CD

Jenkins

Maven

Job description

Amgen in Thousand Oaks, CA seeks a Principal Data Engineer to lead the design, development, and implementation of our data strategy. You will architect robust data platforms, mentor a team of data engineers, and collaborate with business stakeholders to translate data needs into scalable solutions.

The role requires deep knowledge of cloud architectures (AWS/Azure/GCP), Python, PySpark, SQL, and experience building data pipelines.