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Job Description
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:
The 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:
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Design, develop, and maintain data solutions for data generation, collection, and processing
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Be a key team member that assists in design and development of the data pipeline
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Create data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems
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Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions
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Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks
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Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs
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Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency
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Implement data security and privacy measures to protect sensitive data
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Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions
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Collaborate and communicate effectively with product teams
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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
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Identify and resolve complex data-related challenges
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Adhere to best practices for coding, testing, and designing reusable code/component
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Explore new tools and technologies that will help to improve ETL platform performance
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Participate in sprint planning meetings and provide estimations on technical implementation
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Design and develop data pipelines leveraging Databricks, PySpark, and SQL to ingest, transform, and process large-scale datasets.
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Engineer solutions for both structured and unstructured data to enable advanced analytics and insights.
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Implement automated workflows for data ingestion, transformation, and deployment using Databricks Jobs and notebooks, with ongoing monitoring and scheduling.
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Apply performance optimization techniques, including Spark job tuning, caching, partitioning, and indexing, to improve scalability and efficiency.
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Build integrations with multiple data sources, such as SQL databases, APIs, and cloud storage platforms, ensuring seamless connectivity and reliability.
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Collaborate effectively with global teams across time zones to maintain alignment, resolve issues, and deliver on shared objectives.
Basic Qualifications and Experience:
- Bachelor’s / Master’s degree and 4 to 8 years of Computer Science, IT or related field experience
Functional Skills:
Must-Have Skills
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Hands-on experience with big data technologies and platforms, such as Databricks, Apache Spark (Py Spark, SparkSQL), workflow orchestration, performance tuning on big data processing
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Proficiency in data analysis tools (e.g. SQL) and experience with data visualization tools
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Excellent problem-solving skills and the ability to work with large, complex datasets
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Strong understanding of data governance frameworks, tools, and best practices.
Good-to-Have Skills:
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Knowledge of data protection regulations and compliance requirements (e.g., GDPR, CCPA) processing
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Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development
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Strong understanding of data modeling, data warehousing, and data integration concepts
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Knowledge of Python/R, Databricks, SageMaker, cloud data platforms
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Experience implementing automated orchestration and monitoring of data pipelines using Databricks Jobs, Apache Airflow, or similar workflow tools.
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Familiarity with performance optimization techniques for big data processing, such as Spark job tuning, caching, partitioning, and indexing.
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Exposure to multi-source integration involving APIs, SQL databases, and cloud storage platforms.
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Demonstrated ability to collaborate across global teams and time zones, ensuring alignment and delivery in distributed environments.
Professional Certifications (Preferred):
- Certified Data Engineer / Data Analyst (preferred on Databricks or cloud environments)
Soft Skills:
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Excellent critical-thinking and problem-solving skills
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Strong communication and collaboration skills
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Demonstrated awareness of how to function in a team setting
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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.
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
Ready to Apply for the Job?
We highly recommend utilizing Workday's robust Career Profile feature to complete the application process. A link to update your profile is available when you click Apply. You can then complete your Workday profile in minutes with the “Upload My Experience” functionality to upload an updated copy of your resume or you can simply edit the individual sections of your Career Profile.
Please note that you should be in your current position for at least 18 months before applying to internal positions. Staff must notify their current manager if invited for an interview. In addition, Staff are ineligible to apply for open positions if (a) their performance is currently being managed on a performance improvement plan (PIP) or other locally utilized formal coaching document or (b) their most recent performance rating was not a “Partially Meets Expectations” or higher. Please visit our Internal Transfer Guidelines for more detailed information
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About Amgen

Amgen
PublicA biotechnology company that develops and manufactures human therapeutics for various illnesses and diseases.
10,001+
Employees
Thousand Oaks
Headquarters
$138B
Valuation
Reviews
3.6
10 reviews
Work-life balance
3.2
Compensation
4.1
Culture
3.4
Career
2.8
Management
3.5
65%
Recommend to a friend
Pros
Excellent benefits and health benefits
Good pay and compensation
Supportive management and strong leadership
Cons
Limited career growth and promotion opportunities
Work-life balance challenges and long hours
Bureaucratic processes
Salary Ranges
1,244 data points
L2
L3
L4
L5
L6
L2 · Financial Analyst L2
0 reports
$94,068
total per year
Base
$37,627
Stock
$47,034
Bonus
$9,407
$65,848
$122,288
Interview experience
5 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer rate
40%
Experience
Positive 20%
Neutral 80%
Negative 0%
Interview process
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
Technical/Role-Specific Interview
5
Panel Interview
6
Offer
Common questions
Technical Knowledge
Behavioral/STAR
Past Experience
Data Analysis/Statistics
Culture Fit
News & Buzz
Amgen (AMGN) Laps the Stock Market: Here's Why - Yahoo Finance Singapore
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Amgen Inc. $AMGN Shares Sold by Whittier Trust Co. - MarketBeat
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3d ago