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
- Assist 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 standard processes 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’ experience in Computer Science, IT or related field
- 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 in Real World Data/ Health Care
- 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 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
Must-Have Skills
- Big data technologies and platforms (Databricks, Apache Spark (PySpark, SparkSQL), Snowflake, workflow orchestration, performance tuning)
- SQL for data analysis
- ETL tools (Apache Spark, Python packages for data processing and machine learning)
- Data modeling, data warehousing, data integration
- Query performance optimization on big data platforms
- Cloud platforms (AWS preferred)
- Software engineering best-practices (version control, infrastructure-as-code, CI/CD, automated testing)
- Python/R
- Data governance frameworks
- Data protection regulations (GDPR, CCPA)
- Critical-thinking and problem-solving
- Communication and collaboration
- Team functioning
- Presentation skills
What you can expect of us
- Competitive benefits
- Collaborative culture
- Support for professional and personal growth and well-being
- Competitive and comprehensive Total Rewards Plans aligned with local industry standards
Locations
- Hyderabad, India
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
30,000 - 50,000 USD / yearly
Source: xAI estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Big data technologies and platforms (Databricks, Apache Spark (PySpark, SparkSQL), Snowflake, workflow orchestration, performance tuning)intermediate
- SQL for data analysisintermediate
- ETL tools (Apache Spark, Python packages for data processing and machine learning)intermediate
- Data modeling, data warehousing, data integrationintermediate
- Query performance optimization on big data platformsintermediate
- Cloud platforms (AWS preferred)intermediate
- Software engineering best-practices (version control, infrastructure-as-code, CI/CD, automated testing)intermediate
- Python/Rintermediate
- Data governance frameworksintermediate
- Data protection regulations (GDPR, CCPA)intermediate
- Critical-thinking and problem-solvingintermediate
- Communication and collaborationintermediate
- Team functioningintermediate
- Presentation skillsintermediate
Required Qualifications
- Master's degree / bachelor’s degree and 5 to 9 years’ experience in Computer Science, IT or related field (experience)
- 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 (experience)
- Proficiency in data analysis tools (eg. SQL) (experience)
- Proficient in SQL for extracting, transforming, and analyzing complex datasets from relational data stores (experience)
- Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development (experience)
- Strong understanding of data modeling, data warehousing, and data integration concepts (experience)
- Proven ability to optimize query performance on big data platforms (experience)
- Experience in Real World Data/ Health Care (experience)
- Experience with Software engineering best-practices, including but not limited to version control, infrastructure-as-code, CI/CD, and automated testing (experience)
- Knowledge of Python/R, Databricks, SageMaker, cloud data platforms (experience)
- Strong understanding of data governance frameworks, tools, and best practices (experience)
- Knowledge of data protection regulations and compliance requirements (e.g., GDPR, CCPA) (experience)
- Databricks Certificate preferred (experience)
- AWS Data Engineer/Architect (experience)
Responsibilities
- Design, develop, and maintain data solutions for data generation, collection, and processing
- Assist 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 standard processes 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: Support for professional and personal growth and well-being
- general: Competitive and comprehensive Total Rewards Plans 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
- Assist 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 standard processes 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’ experience in Computer Science, IT or related field
- 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 in Real World Data/ Health Care
- 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 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
Must-Have Skills
- Big data technologies and platforms (Databricks, Apache Spark (PySpark, SparkSQL), Snowflake, workflow orchestration, performance tuning)
- SQL for data analysis
- ETL tools (Apache Spark, Python packages for data processing and machine learning)
- Data modeling, data warehousing, data integration
- Query performance optimization on big data platforms
- Cloud platforms (AWS preferred)
- Software engineering best-practices (version control, infrastructure-as-code, CI/CD, automated testing)
- Python/R
- Data governance frameworks
- Data protection regulations (GDPR, CCPA)
- Critical-thinking and problem-solving
- Communication and collaboration
- Team functioning
- Presentation skills
What you can expect of us
- Competitive benefits
- Collaborative culture
- Support for professional and personal growth and well-being
- Competitive and comprehensive Total Rewards Plans aligned with local industry standards
Locations
- Hyderabad, India
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
30,000 - 50,000 USD / yearly
Source: xAI estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Big data technologies and platforms (Databricks, Apache Spark (PySpark, SparkSQL), Snowflake, workflow orchestration, performance tuning)intermediate
- SQL for data analysisintermediate
- ETL tools (Apache Spark, Python packages for data processing and machine learning)intermediate
- Data modeling, data warehousing, data integrationintermediate
- Query performance optimization on big data platformsintermediate
- Cloud platforms (AWS preferred)intermediate
- Software engineering best-practices (version control, infrastructure-as-code, CI/CD, automated testing)intermediate
- Python/Rintermediate
- Data governance frameworksintermediate
- Data protection regulations (GDPR, CCPA)intermediate
- Critical-thinking and problem-solvingintermediate
- Communication and collaborationintermediate
- Team functioningintermediate
- Presentation skillsintermediate
Required Qualifications
- Master's degree / bachelor’s degree and 5 to 9 years’ experience in Computer Science, IT or related field (experience)
- 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 (experience)
- Proficiency in data analysis tools (eg. SQL) (experience)
- Proficient in SQL for extracting, transforming, and analyzing complex datasets from relational data stores (experience)
- Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development (experience)
- Strong understanding of data modeling, data warehousing, and data integration concepts (experience)
- Proven ability to optimize query performance on big data platforms (experience)
- Experience in Real World Data/ Health Care (experience)
- Experience with Software engineering best-practices, including but not limited to version control, infrastructure-as-code, CI/CD, and automated testing (experience)
- Knowledge of Python/R, Databricks, SageMaker, cloud data platforms (experience)
- Strong understanding of data governance frameworks, tools, and best practices (experience)
- Knowledge of data protection regulations and compliance requirements (e.g., GDPR, CCPA) (experience)
- Databricks Certificate preferred (experience)
- AWS Data Engineer/Architect (experience)
Responsibilities
- Design, develop, and maintain data solutions for data generation, collection, and processing
- Assist 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 standard processes 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: Support for professional and personal growth and well-being
- general: Competitive and comprehensive Total Rewards Plans aligned with local industry standards
Tags & Categories