ABOUT AMGEN

Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today.

ABOUT THE ROLE

Role Description:

Let’s do this. Let’s change the world. As a Senior Data Engineer at Amgen, you will be responsible for managing and optimizing the company's data infrastructure and architecture. You will design and implement data pipelines, develop data models, perform data integration, and ensure data quality and governance. Your expertise in data engineering, big data technologies, and data manipulation will contribute to the effective storage, processing, and utilization of large-scale data sets.

Key Responsibilities:

• Design, develop, and maintain scalable ETL/ELT pipelines to support structured, semi-structured, and unstructured data processing across the Enterprise Data Engineering for Biotech or Pharma functional knowledge of R&D.

  
  

• Implement real-time and batch data processing solutions, integrating data from multiple sources into a unified, governed data fabric architecture.

  
  

• Optimize big data processing frameworks using Apache Spark, Hadoop, or similar distributed computing technologies to ensure high availability and cost efficiency.

  
  

• Work with metadata management and data lineage tracking tools to enable enterprise-wide data discovery and governance.

  
  

• Ensure data security, compliance, and role-based access control (RBAC) across data environments.

  
  

• Optimize query performance, indexing strategies, partitioning, and caching for large-scale data sets.

  
  

• Develop CI/CD pipelines for automated data pipeline deployments, version control, and monitoring.

  
  

• Implement data virtualization techniques to provide seamless access to data across multiple storage systems.

  
  

• Collaborate with cross-functional teams, including data architects, business analysts, and DevOps teams, to align data engineering strategies with enterprise goals.

  
  

• Stay up to date with emerging data technologies and best practices, ensuring continuous improvement of Enterprise Data Fabric architectures.

  
  

• Model data for analytics and ML (star/snowflake, Data Vault, semantic layers) and implement robust ELT patterns (dbt or equivalent).

  
  

• Build and maintain a lakehouse/warehouse (e.g., Delta Lake/Iceberg/Hudi; Snowflake/Redshift/BigQuery) with partitioning, clustering, and cost/perf optimization.

  
  

• Orchestrate workflows with Airflow/Azure Data Factory/Prefect and implement CI/CD for data (Git-based deployments, environments, automated tests).

  
  

• Implement data quality and observability (Great Expectations/Deequ, expectations-as-code, lineage/metadata, SLOs and alerting with OpenTelemetry/Prometheus/Datadog).

  
  

• Enforce security and governance (RBAC/ABAC, encryption, secrets, tokenization), manage PII/PHI under GDPR/CCPA and secure SDLC for data.

  
  

• Partner with analytics, data science, and product to define interfaces, SLAs, and contracts; publish clear docs, runbooks, and diagrams.

  
  

• Lead technical discovery, RFCs, and POCs; evaluate vendor tools and guide integrations.

  
  

• Mentor engineers; raise the bar on code quality, reviews, and engineering practices.

  
  

Basic Qualifications and Experience:

• Bachelor’s or Master's degree with 8 - 13 years of experience in Computer Science, IT or related field 

  
  

Must-Have Skills:

• 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, performance tuning on big data processing.

  
  

• Strong understanding of AWS services

  
  

• Experience with Data Fabric, Data Mesh, or similar enterprise-wide data architectures.

  
  

• 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.

  
  

Soft Skills:

• Excellent analytical and troubleshooting skills

  
  

• Strong verbal and written communication skills

  
  

• Ability to work effectively with global, virtual teams

  
  

• High degree of initiative and self-motivation

  
  

• Ability to manage multiple priorities successfully

  
  

• Team-oriented, with a focus on achieving team goals

  
  

• Strong presentation and public speaking skills

  
  

Shift Information:

This position requires you to work a later shift and may be assigned a second or third shift schedule. Candidates must be willing and able to work during evening or night shifts, as required based on business requirements.

EQUAL OPPORTUNITY STATEMENT

Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.

We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.