Data Engineer – R&D Multi-Omics (Open)
Amgen
Data Engineer – R&D Multi-Omics (Open)
Job Description
At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do.
What you will do
- Design, develop, and implement data pipelines, ETL/ELT processes, and data integration solutions
- Contribute to data pipeline projects from inception to deployment, manage scope, timelines, and risks
- Contribute to data models for biopharma scientific data, data dictionaries, and other documentation to ensure data accuracy and consistency
- Optimize large datasets for query performance
- Collaborate with global cross-functional teams including research scientists to understand data requirements and design solutions that meet business needs
- Implement data security and privacy measures to protect sensitive data
- Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions
- Collaborate with Data Architects, Business SMEs, Software Engineers and Data Scientists to design and develop end-to-end data pipelines to meet fast paced business needs across geographic regions
- Identify and resolve 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
- Maintain documentation of processes, systems, and solutions
What we expect of you
- Master’s degree/Bachelors Degree and 5 to 9 years of Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field experience
- 5+ years of experience in designing and supporting biopharma scientific research data analytics (software platforms)
- Databricks Certified Data Engineer Professional preferred
Must-Have Skills
- Proficiency in scientific software development (e.g. Python, R, Rshiny, Plotly Dash, etc)
- Some knowledge of CI/CD processes and cloud computing technologies (e.g. AWS, Google Cloud, etc)
- Proficiency with SQL and Python for data engineering, test automation frameworks (pytest), and scripting tasks
- Hands on experience with big data technologies and platforms, such as Databricks (or equivalent), Apache Spark (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing
- Excellent problem-solving skills and the ability to work with large, complex datasets
- Experience with git, CICD and the software development lifecycle
- Experience with SQL and relational databases (e.g PostgreSQL, MySQL, Oracle) or Databricks
- Experience with cloud computing platforms and infrastructure (AWS preferred)
- Experience using and adopting Agile Framework
- Basic understanding of data modeling, data warehousing, and data integration concepts
- Experience with data visualization tools (e.g. Dash, Plotly, Spotfire)
- Experience with diagramming and collaboration tools such as Miro, Lucidchart or similar tools for process mapping and brainstorming
- Experience writing and maintaining technical documentation in Confluence
- Excellent critical-thinking and problem-solving skills
- Strong communication and collaboration skills
- High degree of initiative and self-motivation
- Demonstrated presentation skills
- Ability to manage multiple priorities successfully
- Team-oriented with a focus on achieving team goals
What you can expect of us
- Competitive benefits
- Collaborative culture
- Competitive and comprehensive Total Rewards Plans that are aligned with local industry standards
Locations
- Hyderabad, India
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
25,000 - 45,000 USD / yearly
Source: xAI estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Proficiency in scientific software development (e.g. Python, R, Rshiny, Plotly Dash, etc)intermediate
- Some knowledge of CI/CD processes and cloud computing technologies (e.g. AWS, Google Cloud, etc)intermediate
- Proficiency with SQL and Python for data engineering, test automation frameworks (pytest), and scripting tasksintermediate
- Hands on experience with big data technologies and platforms, such as Databricks (or equivalent), Apache Spark (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processingintermediate
- Excellent problem-solving skills and the ability to work with large, complex datasetsintermediate
- Experience with git, CICD and the software development lifecycleintermediate
- Experience with SQL and relational databases (e.g PostgreSQL, MySQL, Oracle) or Databricksintermediate
- Experience with cloud computing platforms and infrastructure (AWS preferred)intermediate
- Experience using and adopting Agile Frameworkintermediate
- Basic understanding of data modeling, data warehousing, and data integration conceptsintermediate
- Experience with data visualization tools (e.g. Dash, Plotly, Spotfire)intermediate
- Experience with diagramming and collaboration tools such as Miro, Lucidchart or similar tools for process mapping and brainstormingintermediate
- Experience writing and maintaining technical documentation in Confluenceintermediate
- Excellent critical-thinking and problem-solving skillsintermediate
- Strong communication and collaboration skillsintermediate
- High degree of initiative and self-motivationintermediate
- Demonstrated presentation skillsintermediate
- Ability to manage multiple priorities successfullyintermediate
- Team-oriented with a focus on achieving team goalsintermediate
Required Qualifications
- Master’s degree/Bachelors Degree and 5 to 9 years of Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field experience (experience)
- 5+ years of experience in designing and supporting biopharma scientific research data analytics (software platforms) (experience)
- Databricks Certified Data Engineer Professional preferred (experience)
Responsibilities
- Design, develop, and implement data pipelines, ETL/ELT processes, and data integration solutions
- Contribute to data pipeline projects from inception to deployment, manage scope, timelines, and risks
- Contribute to data models for biopharma scientific data, data dictionaries, and other documentation to ensure data accuracy and consistency
- Optimize large datasets for query performance
- Collaborate with global cross-functional teams including research scientists to understand data requirements and design solutions that meet business needs
- Implement data security and privacy measures to protect sensitive data
- Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions
- Collaborate with Data Architects, Business SMEs, Software Engineers and Data Scientists to design and develop end-to-end data pipelines to meet fast paced business needs across geographic regions
- Identify and resolve 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
- Maintain documentation of processes, systems, and solutions
Benefits
- general: Competitive benefits
- general: Collaborative culture
- general: Competitive and comprehensive Total Rewards Plans that are aligned with local industry standards
Tags & Categories
Data Engineer – R&D Multi-Omics (Open)
Amgen
Data Engineer – R&D Multi-Omics (Open)
Job Description
At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do.
What you will do
- Design, develop, and implement data pipelines, ETL/ELT processes, and data integration solutions
- Contribute to data pipeline projects from inception to deployment, manage scope, timelines, and risks
- Contribute to data models for biopharma scientific data, data dictionaries, and other documentation to ensure data accuracy and consistency
- Optimize large datasets for query performance
- Collaborate with global cross-functional teams including research scientists to understand data requirements and design solutions that meet business needs
- Implement data security and privacy measures to protect sensitive data
- Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions
- Collaborate with Data Architects, Business SMEs, Software Engineers and Data Scientists to design and develop end-to-end data pipelines to meet fast paced business needs across geographic regions
- Identify and resolve 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
- Maintain documentation of processes, systems, and solutions
What we expect of you
- Master’s degree/Bachelors Degree and 5 to 9 years of Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field experience
- 5+ years of experience in designing and supporting biopharma scientific research data analytics (software platforms)
- Databricks Certified Data Engineer Professional preferred
Must-Have Skills
- Proficiency in scientific software development (e.g. Python, R, Rshiny, Plotly Dash, etc)
- Some knowledge of CI/CD processes and cloud computing technologies (e.g. AWS, Google Cloud, etc)
- Proficiency with SQL and Python for data engineering, test automation frameworks (pytest), and scripting tasks
- Hands on experience with big data technologies and platforms, such as Databricks (or equivalent), Apache Spark (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing
- Excellent problem-solving skills and the ability to work with large, complex datasets
- Experience with git, CICD and the software development lifecycle
- Experience with SQL and relational databases (e.g PostgreSQL, MySQL, Oracle) or Databricks
- Experience with cloud computing platforms and infrastructure (AWS preferred)
- Experience using and adopting Agile Framework
- Basic understanding of data modeling, data warehousing, and data integration concepts
- Experience with data visualization tools (e.g. Dash, Plotly, Spotfire)
- Experience with diagramming and collaboration tools such as Miro, Lucidchart or similar tools for process mapping and brainstorming
- Experience writing and maintaining technical documentation in Confluence
- Excellent critical-thinking and problem-solving skills
- Strong communication and collaboration skills
- High degree of initiative and self-motivation
- Demonstrated presentation skills
- Ability to manage multiple priorities successfully
- Team-oriented with a focus on achieving team goals
What you can expect of us
- Competitive benefits
- Collaborative culture
- Competitive and comprehensive Total Rewards Plans that are aligned with local industry standards
Locations
- Hyderabad, India
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
25,000 - 45,000 USD / yearly
Source: xAI estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Proficiency in scientific software development (e.g. Python, R, Rshiny, Plotly Dash, etc)intermediate
- Some knowledge of CI/CD processes and cloud computing technologies (e.g. AWS, Google Cloud, etc)intermediate
- Proficiency with SQL and Python for data engineering, test automation frameworks (pytest), and scripting tasksintermediate
- Hands on experience with big data technologies and platforms, such as Databricks (or equivalent), Apache Spark (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processingintermediate
- Excellent problem-solving skills and the ability to work with large, complex datasetsintermediate
- Experience with git, CICD and the software development lifecycleintermediate
- Experience with SQL and relational databases (e.g PostgreSQL, MySQL, Oracle) or Databricksintermediate
- Experience with cloud computing platforms and infrastructure (AWS preferred)intermediate
- Experience using and adopting Agile Frameworkintermediate
- Basic understanding of data modeling, data warehousing, and data integration conceptsintermediate
- Experience with data visualization tools (e.g. Dash, Plotly, Spotfire)intermediate
- Experience with diagramming and collaboration tools such as Miro, Lucidchart or similar tools for process mapping and brainstormingintermediate
- Experience writing and maintaining technical documentation in Confluenceintermediate
- Excellent critical-thinking and problem-solving skillsintermediate
- Strong communication and collaboration skillsintermediate
- High degree of initiative and self-motivationintermediate
- Demonstrated presentation skillsintermediate
- Ability to manage multiple priorities successfullyintermediate
- Team-oriented with a focus on achieving team goalsintermediate
Required Qualifications
- Master’s degree/Bachelors Degree and 5 to 9 years of Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field experience (experience)
- 5+ years of experience in designing and supporting biopharma scientific research data analytics (software platforms) (experience)
- Databricks Certified Data Engineer Professional preferred (experience)
Responsibilities
- Design, develop, and implement data pipelines, ETL/ELT processes, and data integration solutions
- Contribute to data pipeline projects from inception to deployment, manage scope, timelines, and risks
- Contribute to data models for biopharma scientific data, data dictionaries, and other documentation to ensure data accuracy and consistency
- Optimize large datasets for query performance
- Collaborate with global cross-functional teams including research scientists to understand data requirements and design solutions that meet business needs
- Implement data security and privacy measures to protect sensitive data
- Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions
- Collaborate with Data Architects, Business SMEs, Software Engineers and Data Scientists to design and develop end-to-end data pipelines to meet fast paced business needs across geographic regions
- Identify and resolve 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
- Maintain documentation of processes, systems, and solutions
Benefits
- general: Competitive benefits
- general: Collaborative culture
- general: Competitive and comprehensive Total Rewards Plans that are aligned with local industry standards
Tags & Categories