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Amgen Inc
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Principal Data Engineer Data & Analytics (Global Supply Chain)

Principal Data Engineer Data & Analytics (Global Supply Chain)

Amgen Inc

12 - 17 years

22 - 25 Lacs

hyderabad

Posted:1 hour ago| Platform:

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Skills Required

data analysis data warehousing data architecture data modeling etl process continuous integration python sap supply chain glue amazon redshift presentation skills pyspark ci/cd sql analysis tools athena aws data integration

Work Mode

Work from Office

Job Type

Full Time

Job Description

Role Description:

This role acts as t echnical 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, manag e 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 pipeline s to meet fast paced business need s across geographic regions

Identify and resolve complex data-related challenges

Adhere to best practices for coding, testing , and designing reusable code/component

E xplore 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 AWS services (S3, EMR, Lambda, Glue, UC, Athena, Redshift, EKS), w orkflow 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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Principal Data Engineer Data & Analytics (Global Supply Chain)