
Multinational biopharmaceutical company.
Principal Data Engineer – Data & Analytics (Global Supply Chain)
必須スキル
Databricks
Apache Spark
PySpark
SparkSQL
Delta Lake
AWS
S3
EMR
Lambda
Glue
Athena
Redshift
EKS
SQL
Python
Tableau
Power BI
Git
Jenkins
Infrastructure as Code
Career Category
Information Systems:
Job Description
Role Description:
This role acts as technical architect and hands-on lead for Data Engineering practices across the Smart Supply Chain initiative within Amgen. Additionally, 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 and will architect, build, and optimize enterprise-grade data pipelines using Databricks and AWS-native services.
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, Databricks preferred) to build scalable and efficient data solutions
-
Collaborate and communicate effectively with product teams
-
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
-
Continuously monitor data governance activities and report on compliance, data quality issues, and the effectiveness of governance initiatives
Basic Qualifications and Experience:
- 12 - 17 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 (Databricks (PySpark, SparkSQL, Delta Lake) and AWSservices (S3, EMR, Lambda, Glue, UC, Athena, Redshift, EKS), workflow orchestration, performance tuning on big data processing and the ability to work with large, complex datasets
-
Hands-on experience in orchestrating large-scale data pipelines, performance tuning, lineage tracking, and observability frameworks.
-
Proficiency in data analysis tools (eg. SQL, Python) and experience with data visualization tools (Tableau, Power BI)
-
Excellent problem-solving skills Experience with DevOps practices, version control (Git), CI/CD (Jenkins), and Infrastructure as Code.
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
-
Working knowledge of unstructured data processing, vector stores, and AI-enablement for downstream analytics.
-
Strong understanding of SAP data models (ECC tables) and Supply Chain data domains.
-
Experience working in Agile/SAFe environments with distributed global teams.
Professional Certifications:
-
Certified Data Engineer (preferred on Databricks or cloud environments)
-
Machine Learning 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
.
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Amgenについて

Amgen
PublicA biotechnology company that develops and manufactures human therapeutics for various illnesses and diseases.
10,001+
従業員数
Thousand Oaks
本社所在地
$138B
企業価値
レビュー
24件のレビュー
3.6
24件のレビュー
ワークライフバランス
3.2
報酬
3.5
企業文化
3.1
キャリア
2.8
経営陣
3.4
65%
知人への推奨率
良い点
Excellent benefits and health benefits
Good pay and compensation
Supportive management and leadership
改善点
Limited career growth and promotion opportunities
Work-life balance challenges and long hours
Bureaucratic processes
給与レンジ
1,002件のデータ
L2
L6
L3
L4
L5
L2 · Financial Analyst L2
0件のレポート
$94,068
年収総額
基本給
$37,627
ストック
$47,034
ボーナス
$9,407
$65,848
$122,288
面接レビュー
レビュー5件
難易度
3.0
/ 5
期間
14-28週間
内定率
40%
体験
ポジティブ 20%
普通 80%
ネガティブ 0%
面接プロセス
1
Application Review
2
Recruiter Screen
3
Hiring Manager Interview
4
Technical/Case Interview
5
Final Round/Panel Interview
6
Offer
よくある質問
Technical Knowledge
Behavioral/STAR
Past Experience
Case Study
Culture Fit
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