Sr. Associate Data Engineer
At a glance
Senior Data Engineering role at Amgen. Hyderabad · full-time.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and maintain pipelines that collect, process and move data between systems, using ETL steps to protect data quality
- Create dashboards and self-service analysis in Tableau or Power BI to surface business insights
- Keep data models, dictionaries and supporting records accurate, including materials for product reviews and regulatory inspections
- Explore large datasets, apply feature engineering and help assess, clean and analyze data with other engineers
- Use cloud platforms to develop scalable data solutions and follow practices for tested, reusable code
What you bring
- A relevant bachelor's or master's degree, plus five to eight years in IT, information systems or a related area
- Practical experience with Databricks, PySpark or SparkSQL, workflow orchestration and tuning large-scale data processing
- Experience using Python or R for exploratory analysis, feature engineering and machine-learning model training
- Proficiency in SQL or other data analysis tools, plus experience with visualization platforms such as Tableau or Power BI
Who this fits
This role suits a senior data engineer who can work with large, complex datasets and collaborate across a team. The position is based in Hyderabad, India.
From the employer
Career Category
Information SystemsJob Description
ABOUT AMGEN
At Amgen, our mission to serve patients drives everything we do. We discover, develop, manufacture, and deliver innovative medicines, and we use technology, data, and collaboration to help teams across the enterprise operate with greater speed, quality, and impact.
Role Description:
This role is a key part of Amgen’s 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.
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 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:
- Bachelor’s or Master’s degree in a relevant field (e.g., Computer Science, Engineering or equivalent).
- 5–8 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
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