Jobs
Benefits & Perks
•Healthcare
•401(k)
•Equity
•Flexible Hours
•Remote Work
•Healthcare
•401k
•Equity
•Flexible Hours
•Remote Work
Required Skills
Cloud platforms
Docker
Kubernetes
SQL
Schema Design
Dimensional data modeling
Apache Spark
Databricks
Big data technologies
Career Category
Information Systems:
Job Description
Role Description:
The Sr. Data Engineer designs, develops, and maintains scalable software solutions to address complex business needs, with a focus on building robust data foundations for data repositories, integrations, and reporting. This role ensures system performance and availability while minimizing downtime through automation and proactive incident management.
The ideal candidate will collaborate with product owners, architects, and engineers to design a next-generation metrics engine and implement a new data governance capability, including metadata and reference data management for analytics. Additional responsibilities include designing interfaces, workflows, and data models, conducting data mapping across systems, optimizing data migration, and deploying integrations in development and production environments, ensuring compliance and operational excellence.
This position is perfect for a collaborative, detail-oriented professional passionate about enhancing clinical operations through advanced data engineering and integrations.
Roles & Responsibilities:
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Collaborate closely with product owners, data architects, business SMEs and engineers to develop and deliver high-quality solutions, enhancing and maintaining integrations across clinical systems.
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Design and architect the next-generation metrics engine on modern infrastructure to support operational analytics leveraging cloud technologies.
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Design and implement a new data governance capability incorporating essential features like metadata and reference data management for analytics.
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Take ownership of complex software projects from conception to deployment, managing scope, risk, and timelines.
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Utilize rapid prototyping skills to quickly translate concepts into working solutions and code.
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Leverage modern AI/ML technologies to enable predictive analytics, NLP/NLQ capabilities, and enhance the overall data analytics process.
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Analyze functional and technical requirements of applications, translating them into software architecture and design specifications.
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Develop and execute unit tests, integration tests, and other testing strategies to ensure software quality and reliability.
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Integrate systems and platforms to ensure seamless data flow, functionality, and interoperability.
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Provide ongoing support and maintenance for applications, ensuring smooth and efficient operation.
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Collaborate on building advanced analytics capabilities to empower data-driven decision-making and operational insights.
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Provide technical guidance and mentorship to junior developers, fostering team growth and skill development.
Basic Qualifications and Experience:
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Doctorate Degree OR
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Master’s degree with 6- 11 years of experience in Computer Science, IT or related field OR
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Bachelor’s degree with 8 - 13 years of experience in Computer Science, IT or related field OR
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Diploma with 10 - 12 years of experience in Computer Science, IT or related field
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Diploma with 14 - 18 years of experience in Computer Science, IT or related field
Functional Skills:
Must-Have Skills
-
Strong understanding of cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes)
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Hands on experience writing SQL using any RDBMS (Redshift, Postgres, MySQL, Teradata, Oracle, etc.)
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Experience with Schema Design & Dimensional data modeling
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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
Good-to-Have Skills:
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Experience with software DevOps CI/CD tools, such Git, Jenkins, Linux, and Shell Script
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Experience with Spark, Hive, Kafka, Kinesis, Spark Streaming, and Airflow
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Experience with data flow pipelines to extract, transform, and load data from various data sources in various forms, including custom ETL pipelines
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Experience working in an agile environment (i.e. user stories, iterative development, etc.)
Soft Skills:
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Excellent analytical and troubleshooting skills
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Strong verbal and written communication skills
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Ability to work effectively with global, virtual teams
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High degree of initiative and self-motivation
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Ability to manage multiple priorities successfully
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Team-oriented, with a focus on achieving team goals
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Strong presentation and public speaking skills
.
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About Amgen
Reviews
3.8
2 reviews
Work Life Balance
2.5
Compensation
3.0
Culture
3.0
Career
4.0
Management
3.0
70%
Recommend to a Friend
Pros
Professional development opportunities
Exposure to diverse functions and projects
Large-scale project experience
Cons
Understaffed with high output expectations
Limited permanent job opportunities
Temporary contract limitations
Salary Ranges
1,544 data points
L2
L3
L4
L5
L6
L2 · Financial Analyst L2
0 reports
$94,068
total / year
Base
$37,627
Stock
$47,034
Bonus
$9,407
$65,848
$122,288
Interview Experience
3 interviews
Difficulty
2.7
/ 5
Duration
14-28 weeks
Experience
Positive 0%
Neutral 33%
Negative 67%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Final Round Interview
6
Offer
Common Questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
Past Experience
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