What you will do
Let’s do this. Let’s change the world.
In this vital role as Data Engineer at Amgen, you will play a key role in designing, building, and maintaining scalable data solutions that enable trusted insights and support critical business decisions.
This position is focused on supporting the OUS Field Engagement Team, working closely with stakeholders across the JAPAC and ELMAC regions. You will collaborate with global and regional teams to deliver data solutions that support field operations, customer engagement, and analytics use cases in a complex, multi-region environment.
You will work in an Agile (SAFe) environment, contribute to supporting enterprise data initiatives primarily built on Informatica ETL, including the future migration from Informatica to Databricks.
Key Responsibilities
Design, develop, maintain, and optimize ETL pipelines using Informatica, ensuring high data quality, performance, and reliability
Support and contribute to the future transition of Informatica workloads to Databricks (Spark, Delta Lake)
Build and enhance data pipelines for ingestion, transformation, and processing of large-scale datasets supporting OUS Field Engagement use cases
Collaborate with Data Architects, Business SMEs, Product Owners, and Senior Data Engineers across JAPAC and ELMAC regions to deliver end-to-end data solutions
Participate actively in a SAFe/Agile team, contributing to PI planning, sprint execution, and continuous improvement
Support data governance, metadata management, and data quality initiatives
Identify, troubleshoot, and resolve complex data issues across systems
Apply best practices for coding, testing, documentation, and reusable component design
Translate business and technical requirements into well-structured development tasks
Execute unit and integration testing to ensure solution robustness and compliance with quality standards
Monitor data pipelines and applications, supporting ongoing maintenance and performance optimization
Contribute to CI/CD and DevOps practices for data engineering solutions
Mentor junior team members and promote data engineering best practices
What we expect of you
We are all different, yet we all use our unique contributions to serve patients.
Basic Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Engineering, IT, or a related field
4–7 years of relevant data engineering experience, with strong hands-on ETL background
Preferred Qualifications
Strong experience with Informatica (PowerCenter, IICS)
Exposure to Databricks, Apache Spark, PySpark, or Spark SQL
Familiarity with SAFe or Agile delivery models
Experience or exposure to Master Data Management (MDM)
Experience with Veeva systems (nice to have)
Experience supporting Field Engagement or Commercial data domains (preferred)
Must-Have Skills
Advanced ETL development experience, particularly with Informatica
Strong SQL skills for data extraction, transformation, and analysis
Solid understanding of data modeling and entity relationships
Working knowledge of Python and/or PySpark
Experience supporting production data pipelines and resolving data issues
Ability to work effectively in global, cross-regional teams
Soft Skills
Strong problem-solving and analytical mindset
Excellent communication and collaboration skills, including with global stakeholders across regions
Proven team player with experience in Agile/SAFe environments
High attention to detail and commitment to data quality
Ability to manage priorities and work in a fast-paced environment
Willingness to mentor junior engineers and share knowledge
Adaptable to evolving technologies and business needs
Based on 7,441 disclosed Software salaries on RoleSuite, the role pays a median of $159K/year, with most offers between $125K and $200K (10th–90th percentile: $102K–$235K).
See the full Software salary breakdown →