Senior Data Engineer

About the role

Amgen is looking for a highly motivated Senior Data Engineer to own the design and development of complex data pipelines, solutions and frameworks. The role covers designing, developing and optimizing data pipelines, data integration frameworks and metadata-driven architectures that enable seamless data access and analytics, supporting self-service analytics, AI-driven insights and enterprise-wide data management.

Key responsibilities

• Design, develop and maintain scalable ETL/ELT pipelines for structured, semi-structured and unstructured data across the Enterprise Data Fabric.
• Implement real-time and batch data processing solutions that integrate data from multiple sources into a unified, governed data fabric.
• Optimize big data frameworks such as Apache Spark, Hadoop or similar for high availability and cost efficiency.
• Work with metadata management and data lineage tools to enable data discovery and governance.
• Ensure data security, compliance and role-based access control across data environments.
• Optimize query performance, indexing, partitioning and caching for large data sets.
• Develop CI/CD pipelines for automated deployment, version control and monitoring.
• Implement data virtualization to give seamless access to data across storage systems.
• Collaborate with data architects, business analysts and DevOps teams, and stay current with emerging data technologies.

Required profile

• 9 to 12 years of experience in computer science, IT or a related field.
• Deep expertise in big data processing, distributed computing, data modeling and governance frameworks.
• Ability to quickly learn and adapt to new technologies, with strong problem-solving and analytical skills.
• Experience with Scaled Agile Framework (SAFe), Agile delivery and DevOps practices.
• Preferred: AWS Certified Data Engineer, Databricks certificate and Scaled Agile SAFe certification.

Required skills

• Databricks, PySpark, SparkSQL, Apache Spark, AWS, Python and SQL.
• Workflow orchestration and performance tuning on big data processing.
• Experience with Data Fabric, Data Mesh or similar enterprise data architectures.
• Good to have: API development, SQL/NOSQL and vector databases for large language models, OLAP and OLTP performance tuning, Git, Jenkins, Maven, automated unit testing.