Overview
The R&D Data Catalyst Team is responsible for building Data Searching, Cohort Building, and Knowledge Management tools that provide the Amgen scientific community with visibility to Amgen’s wealth of human datasets, projects and study histories, and knowledge over various scientific findings. These solutions are pivotal tools in Amgen’s goal to accelerate the speed of discovery, and speed to market of advanced precision medications.
The Data Engineer will be responsible for the end-to-end development of an enterprise analytics and data mastering solution leveraging Databricks and Power BI. This role requires expertise in both data architecture and analytics, with the ability to create scalable, reliable, and high-performing enterprise solutions that research cohort-building and advanced research pipeline. The ideal candidate will have experience creating and surfacing large unified repositories of human data, based on integrations from multiple repositories and solutions, and be exceptionally skilled with data analysis and profiling.
You will collaborate closely with stakeholders, product team members, and related IT teams, to design and implement data models, integrate data from various sources, and ensure best practices for data governance and security. The ideal candidate will have a strong background in data warehousing, ETL, Databricks, Power BI, and enterprise data mastering.
Roles & Responsibilities:
Design and build scalable enterprise analytics solutions using Databricks, Power BI, and other modern data tools.
Leverage data virtualization, ETL, and semantic layers to balance need for unification, performance, and data transformation with goal to reduce data proliferation
Break down features into work that aligns with the architectural direction runway
Participate hands-on in pilots and proofs-of-concept for new patterns
Create robust documentation from data analysis and profiling, and proposed designs and data logic
Develop advanced sql queries to profile, and unify data
Develop data processing code in sql, along with semantic views to prepare data for reporting
Develop PowerBI Models and reporting packages
Design robust data models, and processing layers, that support both analytical processing and operational reporting needs.
Design and develop solutions based on best practices for data governance, security, and compliance within Databricks and Power BI environments.
Ensure the integration of data systems with other enterprise applications, creating seamless data flows across platforms.
Develop and maintain Power BI solutions, ensuring data models and reports are optimized for performance and scalability.
Collaborate with stakeholders to define data requirements, functional specifications, and project goals.
Continuously evaluate and adopt new technologies and methodologies to enhance the architecture and performance of data solutions.
Basic Qualifications and Experience:
Master’s degree with 1 to 3 years of experience in Data Engineering OR
Bachelor’s degree with 4 to 5 years of experience in Data Engineering
Diploma and 7 to 9 years of experience in Data Engineering.
Functional Skills:
Must-Have Skills:
Minimum of 3 years of hands-on experience with BI solutions (Preferrable Power BI or Business Objects) including report development, dashboard creation, and optimization.
Minimum of 3 years of hands-on experience building Change-data-capture (CDC) ETL pipelines, data warehouse design and build, and enterprise-level data management.
Hands-on experience with Databricks, including data engineering, optimization, and analytics workloads.
Deep understanding of Power BI, including model design, DAX, and Power Query.
Proven experience designing and implementing data mastering solutions and data governance frameworks.
Expertise in cloud platforms (AWS), data lakes, and data warehouses.
Strong knowledge of ETL processes, data pipelines, and integration technologies.
Strong communication and collaboration skills to work with cross-functional teams and senior leadership.
Ability to assess business needs and design solutions that align with organizational goals.
Exceptional hands-on capabilities with data profiling, data transformation, data mastering
Success in mentoring and training team members
Good-to-Have Skills:
Experience in developing differentiated and deliverable solutions
Experience with human data, ideally human healthcare data
Familiarity with laboratory testing, patient data from clinical care, HL7, FHIR, and/or clinical trial data management
Professional Certifications (please mention if the certification is preferred or mandatory for the role):
ITIL Foundation or other relevant certifications (preferred)
SAFe Agile Practitioner (6.0)
Microsoft Certified: Data Analyst Associate (Power BI) or related certification.
Databricks Certified Professional or similar certification.
Soft Skills:
Excellent analytical and troubleshooting skills
Deep intellectual curiosity
Highest degree of initiative and self-motivation
Strong verbal and written communication skills, including presentation to varied audiences of complex technical/business topics
Confidence technical leader
Ability to work effectively with global, virtual teams, specifically including leveraging of tools and artifacts to assure clear and efficient collaboration across time zones
Ability to manage multiple priorities successfully
Team-oriented, with a focus on achieving team goals
Strong problem solving, analytical skills;
Ability to learn quickly and retain and synthesize complex information from diverse sources
