Data Engineer
Amgen
Data Engineer
Job Description
Join Amgen’s Mission of Serving Patients
What you will do
- 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
- 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 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
What we expect of you
- Master's degree / Bachelor's degree and 5 to 9 years of Computer Science, IT or related field experience
Must-Have Skills
- Hands on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), Snowflake, workflow orchestration, performance tuning on big data processing
- Proficiency in data analysis tools (eg. SQL)
- Proficient in SQL for extracting, transforming, and analyzing complex datasets from relational data stores
- 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
- Proven ability to optimize query performance on big data platforms
- Experience with Software engineering best-practices, including but not limited to version control, infrastructure-as-code, CI/CD, and automated testing
- Knowledge of Python/R, Databricks, SageMaker, cloud data platforms
- Strong knowledge on Oracle / SQL Server, Stored Procedure, PL/SQL
- Knowledge on LINUX OS
- Knowledge on Data visualization and analytics tools like Spotfire, PowerBI
- Strong understanding of data governance frameworks, tools, and best practices
- Knowledge of data protection regulations and compliance requirements (e.g., GDPR, CCPA)
- Databricks Certificate preferred
- AWS Data Engineer/Architect
- 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
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
20,000 - 35,000 USD / yearly
Source: xAI estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Hands on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), Snowflake, workflow orchestration, performance tuning on big data processingintermediate
- Proficiency in data analysis tools (eg. SQL)intermediate
- Proficient in SQL for extracting, transforming, and analyzing complex datasets from relational data storesintermediate
- Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model developmentintermediate
- Strong understanding of data modeling, data warehousing, and data integration conceptsintermediate
- Proven ability to optimize query performance on big data platformsintermediate
- Experience with Software engineering best-practices, including but not limited to version control, infrastructure-as-code, CI/CD, and automated testingintermediate
- Knowledge of Python/R, Databricks, SageMaker, cloud data platformsintermediate
- Strong knowledge on Oracle / SQL Server, Stored Procedure, PL/SQLintermediate
- Knowledge on LINUX OSintermediate
- Knowledge on Data visualization and analytics tools like Spotfire, PowerBIintermediate
- Strong understanding of data governance frameworks, tools, and best practicesintermediate
- Knowledge of data protection regulations and compliance requirements (e.g., GDPR, CCPA)intermediate
- Databricks Certificate preferredintermediate
- AWS Data Engineer/Architectintermediate
- Excellent critical-thinking and problem-solving skillsintermediate
- Strong communication and collaboration skillsintermediate
- Demonstrated awareness of how to function in a team settingintermediate
- Demonstrated presentation skillsintermediate
Required Qualifications
- Master's degree / Bachelor's degree and 5 to 9 years of Computer Science, IT or related field experience (experience)
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
- 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 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
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
Amgen
Data Engineer
Job Description
Join Amgen’s Mission of Serving Patients
What you will do
- 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
- 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 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
What we expect of you
- Master's degree / Bachelor's degree and 5 to 9 years of Computer Science, IT or related field experience
Must-Have Skills
- Hands on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), Snowflake, workflow orchestration, performance tuning on big data processing
- Proficiency in data analysis tools (eg. SQL)
- Proficient in SQL for extracting, transforming, and analyzing complex datasets from relational data stores
- 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
- Proven ability to optimize query performance on big data platforms
- Experience with Software engineering best-practices, including but not limited to version control, infrastructure-as-code, CI/CD, and automated testing
- Knowledge of Python/R, Databricks, SageMaker, cloud data platforms
- Strong knowledge on Oracle / SQL Server, Stored Procedure, PL/SQL
- Knowledge on LINUX OS
- Knowledge on Data visualization and analytics tools like Spotfire, PowerBI
- Strong understanding of data governance frameworks, tools, and best practices
- Knowledge of data protection regulations and compliance requirements (e.g., GDPR, CCPA)
- Databricks Certificate preferred
- AWS Data Engineer/Architect
- 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
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
20,000 - 35,000 USD / yearly
Source: xAI estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Hands on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), Snowflake, workflow orchestration, performance tuning on big data processingintermediate
- Proficiency in data analysis tools (eg. SQL)intermediate
- Proficient in SQL for extracting, transforming, and analyzing complex datasets from relational data storesintermediate
- Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model developmentintermediate
- Strong understanding of data modeling, data warehousing, and data integration conceptsintermediate
- Proven ability to optimize query performance on big data platformsintermediate
- Experience with Software engineering best-practices, including but not limited to version control, infrastructure-as-code, CI/CD, and automated testingintermediate
- Knowledge of Python/R, Databricks, SageMaker, cloud data platformsintermediate
- Strong knowledge on Oracle / SQL Server, Stored Procedure, PL/SQLintermediate
- Knowledge on LINUX OSintermediate
- Knowledge on Data visualization and analytics tools like Spotfire, PowerBIintermediate
- Strong understanding of data governance frameworks, tools, and best practicesintermediate
- Knowledge of data protection regulations and compliance requirements (e.g., GDPR, CCPA)intermediate
- Databricks Certificate preferredintermediate
- AWS Data Engineer/Architectintermediate
- Excellent critical-thinking and problem-solving skillsintermediate
- Strong communication and collaboration skillsintermediate
- Demonstrated awareness of how to function in a team settingintermediate
- Demonstrated presentation skillsintermediate
Required Qualifications
- Master's degree / Bachelor's degree and 5 to 9 years of Computer Science, IT or related field experience (experience)
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
- 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 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
Benefits
- general: Competitive benefits
- general: Collaborative culture
- general: Competitive and comprehensive Total Rewards Plans that are aligned with local industry standards
Tags & Categories