Sr. Associate Data Engineer

Amgen Technology; Hyderabad; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Amgen in Hyderabad is seeking a Global Supply Chain Analytics professional to develop data and AI-driven solutions for the Supply Chain Business. You will design, build, and manage data, analyze it for insights, and create reports to support governance and decision making.

The role requires strong technical skills in big data, data architecture, ETL, and visualization with Tableau or Power BI, with experience in cloud platforms such as AWS.

Qualifications

• Bachelors or Masters degree in Computer Science, Engineering or equivalent.
• Experience in the global pharmaceutical industry preferred.

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 creation of metric dashboards, self-serve analytics, and business insights using Tableau or Power BI.
• Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency.
• Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions.
• Adhere to best practices for coding, testing, and designing reusable code/component.
• Exploratory data analysis, understand business knowledge, do feature engineering.
• Support generation of annual product review documents, regulatory inspections, and process documentation.
• Work with data engineers on data quality assessment, data cleansing and data analytics.

Skills

Big data analytics

Python

SQL

Tableau/Power BI

Problem solving

Education

Bachelor's or Master's in CS/Engineering

Tools

Databricks

SparkSQL

Power BI

Tableau

Python

SQL

Job description

Job Summary

This role is a key part of Amgens Global Supply Chain Analytics team, developing data and AI-driven solutions for Supply Chain Business. Responsibilities include designing, building, and managing data, analyzing it for actionable insights, creating reports, supporting data governance, and visualizing information to ensure reliable and efficient data management. The ideal candidate has strong technical skills, experience with big data, and a solid understanding of data architecture and ETL processes.

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 creation of metric dashboards, self-serve analytics, and business insights using Tableau or Power BI
• Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency
• Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions
• Adhere to best practices for coding, testing, and designing reusable code/component
• Exploratory data analysis, understand business knowledge, do feature engineering
• Support generation of annual product review documents, regulatory inspections, and process documentation
• Work with data engineers on data quality assessment, data cleansing and data analytics

Basic Qualifications and Experience

• Bachelors or Masters degree in a relevant field (e.g., Computer Science, Engineering or equivalent).
• 58 years of work experience in Information Technology, Information Systems, or a related field
• Experience in the global pharmaceutical industry preferred.

Functional Skills

Must-Have Skills

• Hands on experience with big data technologies and platforms, such as Databricks (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing
• Hands on experience with various Python/R packages for EDA, feature engineering and machine learning model training
• Proficiency in data analysis tools (eg. SQL) and experience with data visualization tools
• Proficiency with data visualization platforms like Tableau, Power BI, or matplotlib/seaborn for Python
• Excellent problem-solving skills and the ability to work with large, complex datasets

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
• Interest in GenAI/LLM technology and building data products that support natural language interfaces

Professional Certifications

• Certified Data Analytics professional

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