below marketmost similar roles pay hereabove market
This role pays less than
62%
of similar roles. Most pay
$185,276–$261,325
— the blue band above.
At the midpoint, this role pays about
$202k
versus about
$223k
for comparable roles.
Based on 240 similar postings.
Employer
About Amgen
Amgen is a leading biotechnology company that discovers, develops, manufactures, and delivers innovative human therapeutics, with products addressing conditions such as anemia, bone loss, inflammation, and cancer. Industry: Biotechnology & Pharmaceuticals
Amgen currently has
76 open roles
on FindRole.
Listed pay typically runs
$136,906–$185,227
across 45 roles with salary data.
The Associate Director - Information Systems serves as the product leader for the Clinical Data Hub within the Clinical Design and Analysis organization. This role involves setting the product vision, strategy, and multi-year roadmap for a scalable clinical data foundation designed to enable discovery, integration, governance, and reuse of clinical development data. Key responsibilities include managing the product backlog, leading a cross-functional team, and establishing senior partnerships across Clinical Development and Data Management. The position requires expertise in modern data architecture, including cloud, data lakes, APIs, and metadata. Preferred technical skills include AWS, Databricks, Apache technologies, Python, R, SQL, Docker, and GitLab. The role solves critical business problems by accelerating study onboarding, improving data quality, and enabling analytics and AI-ready data for faster product development.
Set the product vision, strategy, and multi-year roadmap for the Clinical Data Hub.
Establish senior partnerships across Clinical Development, Data Management, Biostatistics, and other key functions.
Champion scalable data products, common data standards, metadata, governance, and security capabilities.
Manage the product backlog, budget, and investment priorities while making trade-off decisions on technical debt and compliance.
Provide strategic and people leadership for a cross-functional product team to develop technical and delivery capabilities.
Develop workforce and resource strategies, including talent development, succession planning, and vendor management.
Establish product governance and performance management practices based on business outcomes, cost, and quality.
Represent the Clinical Data Hub in senior leadership forums to communicate strategy, risks, and investment needs.
What we're looking for
Must have a Doctorate with 4 years, Master’s with 8 years, Bachelor’s with 10 years, or Associate’s with 12 years of experience in Information Systems, Computer Science, or Biology.
Must have a High school diploma or GED with 14 years of experience in Information Systems, Computer Science, or Biology.
Must have a minimum of 4 years of managerial experience directly managing people or leading teams, products, programs, or resource allocation.
Domain knowledge of Clinical Development data and processes, including data management, study execution, and regulated environments (preferred).
Product Management or Product Owner experience leading enterprise data, analytics, or platform products (preferred).
Experience with product strategy, multi-year roadmaps, portfolio prioritization, and Agile product delivery (preferred).
Strong understanding of modern data architecture, including cloud, data lakes, APIs, metadata, security, and DevOps (preferred).
Experience with AWS, Databricks, Apache technologies, Python, R, SQL, Docker, and GitLab (preferred).
AWS
Databricks
Python
SQL
Apache Spark
Generative AI
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Machine Learning
Cloud-native data engineering
Agile
SAFe
Data Governance
Data Pipelines
Product Roadmap
Spec-Driven Development (SDD)
Snowflake
Data Strategy
Data Product Management
Data Governance
Metadata Management
Data Engineering
Business Intelligence
AI
UAT
Source-to-Target Mapping
Data Quality
Cloud Data Platforms
Analytics Enablement
Veeva
Salesforce
Medidata
AWS
Azure
Google Cloud
Tableau
Power BI
Looker
Qlik
ThoughtSpot
ETL
APIs
Data Lakes
Data Warehouses
AI/ML
Serverless
SDLC
GxP
User Acceptance Testing
Data Analytics
Business Intelligence
Veeva
Salesforce
Medidata
AWS
Azure
Google Cloud
Tableau
Power BI
Looker
Qlik
ThoughtSpot
ETL
APIs
Data Lakes
Data Warehouses
AI/ML
Serverless Computing
SDLC
GxP
User Acceptance Testing
Data Analytics
Business Intelligence
Generative AI
Machine Learning
MLOps
Python
R
Scala
Java
AWS
Azure
Databricks
Causal Inference
Optimization
Predictive Modeling
Model Governance
Data Science
Statistics
Econometrics
Operations Research
Machine Learning
Python
R
Deep Learning
Mechanistic Modelling
PK/PD
QSP
PyTorch
Keras
scikit-learn
Pandas
SQL
Data Science
Statistics
Data Visualization
Exploratory Data Analysis
Version Control
NLP
GenAI