Amgen Inc. is looking for a highly motivated expert Data Engineer to join our Manufacturing Applications Product Team. In this role, you will design, develop, and optimize advanced data pipelines and frameworks to enable seamless data access and analytics for critical Manufacturing and Operations use cases.

What You'll Do

Design, develop, and maintain complex ETL/ELT data pipelines in Databricks using PySpark, Scala, and SQL to process large-scale datasets.
Build highly efficient data pipelines to migrate and deploy complex data across systems, with an understanding of biotech, pharma, or manufacturing domains.
Design and implement solutions to enable unified data access, governance, and interoperability across hybrid cloud environments.
Ingest and transform structured and unstructured data from databases (PostgreSQL, MySQL, SQL Server, MongoDB, etc.), APIs, logs, event streams, images, PDFs, and third-party platforms.
Ensure data integrity, accuracy, and consistency through rigorous quality checks and monitoring.
Innovate, explore, and implement new tools and technologies to enhance efficient data processing.
Proactively identify and implement opportunities to automate tasks and develop reusable frameworks.
Work in an Agile and Scaled Agile (SAFe) environment, collaborating with cross-functional teams, product owners, and Scrum Masters to deliver incremental value.
Use JIRA, Confluence, and Agile DevOps tools to manage sprints, backlogs, and user stories.
Support continuous improvement, test automation, and DevOps practices in the data engineering lifecycle.
Collaborate and communicate effectively with product teams and cross-functional teams to understand business requirements and translate them into technical solutions.

What We're Looking For

Hands-on experience in data engineering technologies such as Databricks, PySpark, SparkSQL, Apache Spark, AWS, Python, SQL, and Scaled Agile methodologies.
Proficiency in workflow orchestration and performance tuning on big data processing.
Strong understanding of AWS services.
Ability to quickly learn, adapt, and apply new technologies.
Strong problem-solving and analytical skills.
Excellent communication and teamwork skills.
Experience with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices.
Experience with streaming technologies such as Apache Kafka, Debezium, or similar platforms for real-time data processing and integration.
A Master’s degree and 3 to 4+ years of Computer Science, IT, or related field experience OR a Bachelor’s degree and 5 to 8+ years of Computer Science, IT, or related field experience.

Nice to Have

AWS Certified Data Engineer.
Databricks Certificate.
Scaled Agile SAFe certification.
Experience with AI assisted code development using tools like GitHub Copilot, Cursor, or Claude Code.
Data engineering experience in biotechnology or pharma industry.
Experience in writing APIs to make data available to consumers.
Experience with SQL/NoSQL databases and vector databases for large language models.
Experience with data modeling and performance tuning for both OLAP and OLTP databases.
Experience with software engineering best practices, including version control (Git, Subversion), CI/CD (Jenkins, Maven), automated unit testing, and DevOps.
Experience with manufacturing related data sources like SCADA or Data Historian.