Sr. Data Engineer – Clinical Data Hub

Career Category

Information Systems

Job Description

ABOUT THE ROLE

Clinical Data Hub

Amgen’s Clinical Data Hub (CDH) is a Information Technology product team chartered to identify, design and implement technology that powers Amgen’s end‑to‑end drug development lifecycle. We are at an inflection point, accelerating through rapid, AI‑driven modernization to build clinical data products that enable both drug regulatory submissions and drug discovery and development. If you’re passionate about turning complex clinical data into resilient, scalable products that help speed life‑changing medicines to patients worldwide, this is a once‑in‑a‑decade opportunity to do your career‑best work on a global stage.

Role Description:

he role is responsible for designing, building, maintaining, analyzing, and interpreting data to provide actionable insights that drive business decisions. This role involves working with large datasets, developing reports, supporting and executing data governance initiatives and, visualizing data to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has strong technical skills, experience with big data technologies, and a deep understanding of data architecture and ETL processes

Roles & Responsibilities:

Design, develop, and maintain data solutions for data generation, collection, and processing

Be a key team member that assists in design and development of the data pipeline

Create data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems

Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions

Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks

Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs

Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency

Implement data security and privacy measures to protect sensitive data

Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions

Collaborate with Data Architects, Business SMEs, and Data Scientists to design and develop end-to-end data pipelines to meet fast paced business needs across geographic regions

Identify and resolve complex data-related challenges

Adhere to best practices for coding, testing, and designing reusable code/component

Explore new tools and technologies that will help to improve ETL platform performance

Participate in sprint planning meetings and provide estimations on technical implementation

Collaborate and communicate effectively with product teams

Basic Qualifications and Experience:

Master’s or Bachelor's degree with 8 - 12 years of experience in Computer Science, IT or related field

Functional Skills:

Must-Have Skills:

Hands on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing

Hands on experience with various Python/R packages for EDA, feature engineering and machine learning model training

Proficiency in data analysis tools (eg. SQL) and experience with data visualization tools

Excellent problem-solving skills and the ability to work with large, complex datasets

Strong understanding of data governance frameworks, tools, and best practices.

Knowledge of data protection regulations and compliance requirements (e.g., GDPR, CCPA)

Good-to-Have Skills:

Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development

Strong understanding of data modeling, data warehousing, and data integration concepts

Knowledge of Python/R, Databricks, SageMaker, cloud data platforms

Clinical development domain knowledge is a plus

Professional Certifications:

Certified Data Engineer / Data Analyst (preferred on Databricks or cloud environments)

Certified Data Scientist (preferred on Databricks or Cloud environments)

Machine Learning Certification (preferred on Databricks or Cloud environments)

SAFe for Teams certification (preferred)

Soft Skills:

Excellent critical-thinking and problem-solving skills

Strong communication and collaboration skills

Demonstrated awareness of how to function in a team setting

Demonstrated presentation 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.

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