Sr Data Engineer
Amgen
Sr Data Engineer
Job Description
Career CategoryInformation SystemsJob DescriptionABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, making people’s lives easier, fuller, and longer. We discover, develop, manufacture, and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting edge of innovation, using technology and human genetic data to push beyond what’s known today. ABOUT THE ROLE Role Description: Let’s do this. Let’s change the world. We are looking for highly motivated expert Senior Data Engineer who can own the design & development of complex data pipelines, solutions and frameworks with detailed functional knowledge of R&D. The ideal candidate will be responsible to design, develop, and optimize data pipelines, data integration frameworks, and metadata-driven architectures that enable seamless data access and analytics. This role prefers deep expertise in big data processing, distributed computing, data modeling, and governance frameworks to support self-service analytics, AI-driven insights, and enterprise-wide data management. Roles & Responsibilities: Design, develop, and maintain scalable ETL/ELT pipelines to support structured, semi-structured, and unstructured data processing across the Enterprise Data Engineering for Biotech or Pharma functional knowledge of R&D. Implement real-time and batch data processing solutions, integrating data from multiple sources into a unified, governed data fabric architecture. Optimize big data processing frameworks using Apache Spark, Hadoop, or similar distributed computing technologies to ensure high availability and cost efficiency. Work with metadata management and data lineage tracking tools to enable enterprise-wide data discovery and governance. Ensure data security, compliance, and role-based access control (RBAC) across data environments. Optimize query performance, indexing strategies, partitioning, and caching for large-scale data sets. Develop CI/CD pipelines for automated data pipeline deployments, version control, and monitoring. Implement data virtualization techniques to provide seamless access to data across multiple storage systems. Collaborate with cross-functional teams, including data architects, business analysts, and DevOps teams, to align data engineering strategies with enterprise goals. Stay up to date with emerging data technologies and best practices, ensuring continuous improvement of Enterprise Data Fabric architectures. Must-Have Skills: Hands-on experience in data engineering technologies such as Databricks, PySpark, SparkSQL Apache Spark, AWS, Python, SQL, and Scaled Agile methodologies. Proficiency in workflow orchestration, performance tuning on big data processing. Strong understanding of AWS services Experience with Data Fabric, Data Mesh, or similar enterprise-wide data architectures. Ability to quickly learn, adapt and apply new technologies Strong problem-solving and analytical skills Excellent communication and teamwork skills Experience with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices. Good-to-Have Skills: Good to have deep expertise in Biotech & Pharma industries Experience in writing APIs to make the data available to the consumers Experienced with SQL/NOSQL database, vector database for large language models Experienced with data modeling and performance tuning for both OLAP and OLTP databases Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops Education and Professional Certifications Master’s degree and 3 to 4 + years of relevant Computer Science, IT or related field experience OR Bachelor’s degree and 5 to 8 + years of relevant Computer Science, IT or related field experience AWS Certified Data Engineer preferred Databricks Certificate preferred Scaled Agile SAFe certification preferred Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Ability to learn quickly, be organized and detail oriented. Strong presentation and public speaking skills. Ready to Apply for the Job? We highly recommend utilizing Workday's robust Career Profile feature to complete the application process. A link to update your profile is available when you click Apply. You can then complete your Workday profile in minutes with the “Upload My Experience” functionality to upload an updated copy of your resume or you can simply edit the individual sections of your Career Profile. Please note that you should be in your current position for at least 18 months before applying to internal positions. Staff must notify their current manager if invited for an interview. In addition, Staff are ineligible to apply for open positions if (a) their performance is currently being managed on a performance improvement plan (PIP) or other locally utilized formal coaching document or (b) their most recent performance rating was not a “Partially Meets Expectations” or higher. Please visit our Internal Transfer Guidelines for more detailed information .
Locations
- India - Hyderabad
Skills Required
- Biotech & Pharma industriesintermediate
- writing APIs to make the data available to the consumersintermediate
Preferred Qualifications
- Good to have deep expertise in Biotech & Pharma industries (experience)
- Experience in writing APIs to make the data available to the consumers (experience)
- Experience in writing APIs to make the data available to the consumers (experience)
- Experienced with SQL/NOSQL database, vector database for large language models (experience)
- Experienced with SQL/NOSQL database, vector database for large language models (experience)
- Experienced with data modeling and performance tuning for both OLAP and OLTP databases (experience)
- Experienced with data modeling and performance tuning for both OLAP and OLTP databases (experience)
- Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops (experience)
- Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops (experience)
- Education and Professional Certifications (certification)
- Master’s degree and 3 to 4 + years of relevant Computer Science, IT or related field experience OR (experience)
- Master’s degree and 3 to 4 + years of relevant Computer Science, IT or related field experience OR (experience)
- Bachelor’s degree and 5 to 8 + years of relevant Computer Science, IT or related field experience (experience)
- Bachelor’s degree and 5 to 8 + years of relevant Computer Science, IT or related field experience (experience)
- AWS Certified Data Engineer preferred (certification)
- Databricks Certificate preferred (experience)
- Scaled Agile SAFe certification preferred (certification)
- Excellent analytical and troubleshooting skills. (experience)
- Excellent analytical and troubleshooting skills. (experience)
- Strong verbal and written communication skills (experience)
- Strong verbal and written communication skills (experience)
- Ability to work effectively with global, virtual teams (experience)
- Ability to work effectively with global, virtual teams (experience)
- High degree of initiative and self-motivation. (degree)
- High degree of initiative and self-motivation. (degree)
- Ability to manage multiple priorities successfully. (experience)
- Ability to manage multiple priorities successfully. (experience)
- Team-oriented, with a focus on achieving team goals. (experience)
- Team-oriented, with a focus on achieving team goals. (experience)
- Ability to learn quickly, be organized and detail oriented. (experience)
- Ability to learn quickly, be organized and detail oriented. (experience)
- Strong presentation and public speaking skills. (experience)
- Strong presentation and public speaking skills. (experience)
- Ready to Apply for the Job? (experience)
- We highly recommend utilizing Workday's robust Career Profile feature to complete the application process. A link to update your profile is available when you click Apply. You can then complete your Workday profile in minutes with the “Upload My Experience” functionality to upload an updated copy of your resume or you can simply edit the individual sections of your Career Profile. (experience)
- Please note that you should be in your current position for at least 18 months before applying to internal positions. Staff must notify their current manager if invited for an interview. In addition, Staff are ineligible to apply for open positions if (a) their performance is currently being managed on a performance improvement plan (PIP) or other locally utilized formal coaching document or (b) their most recent performance rating was not a “Partially Meets Expectations” or higher. Please visit our Internal Transfer Guidelines for more detailed information (experience)
Responsibilities
- Design, develop, and maintain scalable ETL/ELT pipelines to support structured, semi-structured, and unstructured data processing across the Enterprise Data Engineering for Biotech or Pharma functional knowledge of R&D.
- Design, develop, and maintain scalable ETL/ELT pipelines to support structured, semi-structured, and unstructured data processing across the Enterprise Data Engineering for Biotech or Pharma functional knowledge of R&D.
- Implement real-time and batch data processing solutions, integrating data from multiple sources into a unified, governed data fabric architecture.
- Implement real-time and batch data processing solutions, integrating data from multiple sources into a unified, governed data fabric architecture.
- Optimize big data processing frameworks using Apache Spark, Hadoop, or similar distributed computing technologies to ensure high availability and cost efficiency.
- Optimize big data processing frameworks using Apache Spark, Hadoop, or similar distributed computing technologies to ensure high availability and cost efficiency.
- Work with metadata management and data lineage tracking tools to enable enterprise-wide data discovery and governance.
- Work with metadata management and data lineage tracking tools to enable enterprise-wide data discovery and governance.
- Ensure data security, compliance, and role-based access control (RBAC) across data environments.
- Ensure data security, compliance, and role-based access control (RBAC) across data environments.
- Optimize query performance, indexing strategies, partitioning, and caching for large-scale data sets.
- Optimize query performance, indexing strategies, partitioning, and caching for large-scale data sets.
- Develop CI/CD pipelines for automated data pipeline deployments, version control, and monitoring.
- Develop CI/CD pipelines for automated data pipeline deployments, version control, and monitoring.
- Implement data virtualization techniques to provide seamless access to data across multiple storage systems.
- Implement data virtualization techniques to provide seamless access to data across multiple storage systems.
- Collaborate with cross-functional teams, including data architects, business analysts, and DevOps teams, to align data engineering strategies with enterprise goals.
- Collaborate with cross-functional teams, including data architects, business analysts, and DevOps teams, to align data engineering strategies with enterprise goals.
- Stay up to date with emerging data technologies and best practices, ensuring continuous improvement of Enterprise Data Fabric architectures.
- Stay up to date with emerging data technologies and best practices, ensuring continuous improvement of Enterprise Data Fabric architectures.
- Must-Have Skills:
- Hands-on experience in data engineering technologies such as Databricks, PySpark, SparkSQL Apache Spark, AWS, Python, SQL, and Scaled Agile methodologies.
- Hands-on experience in data engineering technologies such as Databricks, PySpark, SparkSQL Apache Spark, AWS, Python, SQL, and Scaled Agile methodologies.
- Proficiency in workflow orchestration, performance tuning on big data processing.
- Proficiency in workflow orchestration, performance tuning on big data processing.
- Strong understanding of AWS services
- Strong understanding of AWS services
- Experience with Data Fabric, Data Mesh, or similar enterprise-wide data architectures.
- Experience with Data Fabric, Data Mesh, or similar enterprise-wide data architectures.
- Ability to quickly learn, adapt and apply new technologies
- Ability to quickly learn, adapt and apply new technologies
- Strong problem-solving and analytical skills
- Strong problem-solving and analytical skills
- Excellent communication and teamwork skills
- Excellent communication and teamwork skills
- Experience with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices.
- Experience with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices.
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