Data Engineer
Amgen
Data Engineer
Job Description
Career CategoryInformation SystemsJob DescriptionJoin Amgen’s Mission of Serving PatientsAt 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.Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career. What you will doLet’s do this. Let’s change the world. In this vital role you 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.Design, develop, and maintain complex ETL/ELT data pipelines in Databricks using PySpark, Scala, and SQL to process large-scale datasetsUnderstand the biotech/pharma or related domains & build highly efficient data pipelines to migrate and deploy complex data across systemsDesign and Implement solutions to enable unified data access, governance, and interoperability across hybrid cloud environmentsIngest and transform structured and unstructured data from databases (PostgreSQL, MySQL, SQL Server, MongoDB etc.), APIs, logs, event streams, images, pdf, and third-party platformsEnsuring data integrity, accuracy, and consistency through rigorous quality checks and monitoringExpert in data quality, data validation and verification frameworksInnovate, explore and implement new tools and technologies to enhance efficient data processingProactively identify and implement opportunities to automate tasks and develop reusable frameworksWork in an Agile and Scaled Agile (SAFe) environment, collaborating with cross-functional teams, product owners, and Scrum Masters to deliver incremental valueUse JIRA, Confluence, and Agile DevOps tools to manage sprints, backlogs, and user storiesSupport continuous improvement, test automation, and DevOps practices in the data engineering lifecycleCollaborate and communicate effectively with the product teams, with cross-functional teams to understand business requirements and translate them into technical solutionsWhat we expect of youWe are all different, yet we all use our unique contributions to serve patients. We are looking for highly motivated expert Data Engineer who can own the design & development of complex data pipelines, solutions and frameworks.Basic Qualifications:Master’s degree and 1 to 3 years of Computer Science, IT or related field experience ORBachelor’s degree and 3 to 5 years of Computer Science, IT or related field experience ORDiploma and 7 to 9 years of Computer Science, IT or related field experienceHands-on experience in data engineering technologies such as Databricks, PySpark, SparkSQL Apache Spark, AWS, Python, SQL, and Scaled Agile methodologiesProficiency in workflow orchestration, performance tuning on big data processingStrong understanding of AWS servicesAbility to quickly learn, adapt and apply new technologiesStrong problem-solving and analytical skillsExcellent communication and teamwork skillsExperience with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practicesPreferred Qualifications:AWS Certified Data Engineer preferredDatabricks Certificate preferredScaled Agile SAFe certification preferredData Engineering experience in Biotechnology or pharma industryExperience in writing APIs to make the data available to the consumersExperienced with SQL/NOSQL database, vector database for large language modelsExperienced with data modeling and performance tuning for both OLAP and OLTP databasesExperienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and DevOpsSoft Skills:Excellent analytical and troubleshooting skills.Strong verbal and written communication skillsAbility to work effectively with global, virtual teamsHigh 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.What you can expect of usAs we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way.In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards.Apply now and make a lasting impact with the Amgen team. careers.amgen.comAs an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease.Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation..
Locations
- India - Hyderabad
Skills Required
- data engineering technologies such as Databricksintermediate
- workflow orchestrationintermediate
- Scaled Agile Frameworkintermediate
- Biotechnologyintermediate
- writing APIs to make the data available to the consumersintermediate
Required Qualifications
- Master’s degree and 1 to 3 years of Computer Science, IT or related field experience OR (experience, 3 years)
- Bachelor’s degree and 3 to 5 years of Computer Science, IT or related field experience OR (experience, 5 years)
- Diploma and 7 to 9 years of Computer Science, IT or related field experience (experience, 9 years)
- Hands-on experience in data engineering technologies such as Databricks, PySpark, SparkSQL Apache Spark, AWS, Python, SQL, and Scaled Agile methodologies (experience)
- Proficiency in workflow orchestration, performance tuning on big data processing (experience)
- Strong understanding of AWS services (experience)
- Ability to quickly learn, adapt and apply new technologies (experience)
- Strong problem-solving and analytical skills (experience)
- Excellent communication and teamwork skills (experience)
- Experience with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices (experience)
- Master’s degree and 1 to 3 years of Computer Science, IT or related field experience OR (experience, 3 years)
- Bachelor’s degree and 3 to 5 years of Computer Science, IT or related field experience OR (experience, 5 years)
- Diploma and 7 to 9 years of Computer Science, IT or related field experience (experience, 9 years)
- Hands-on experience in data engineering technologies such as Databricks, PySpark, SparkSQL Apache Spark, AWS, Python, SQL, and Scaled Agile methodologies (experience)
- Proficiency in workflow orchestration, performance tuning on big data processing (experience)
- Strong understanding of AWS services (experience)
- Ability to quickly learn, adapt and apply new technologies (experience)
- Strong problem-solving and analytical skills (experience)
- Excellent communication and teamwork skills (experience)
- Experience with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices (experience)
Preferred Qualifications
- AWS Certified Data Engineer preferred (certification)
- Databricks Certificate preferred (experience)
- Scaled Agile SAFe certification preferred (certification)
- Data Engineering experience in Biotechnology or pharma industry (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 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 DevOps (experience)
- Data Engineering experience in Biotechnology or pharma industry (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 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 DevOps (experience)
Responsibilities
- Let’s do this. Let’s change the world. In this vital role you 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.
- Design, develop, and maintain complex ETL/ELT data pipelines in Databricks using PySpark, Scala, and SQL to process large-scale datasets
- Understand the biotech/pharma or related domains & build highly efficient data pipelines to migrate and deploy complex data across systems
- Design and Implement solutions to enable unified data access, governance, and interoperability across hybrid cloud environments
- Ingest and transform structured and unstructured data from databases (PostgreSQL, MySQL, SQL Server, MongoDB etc.), APIs, logs, event streams, images, pdf, and third-party platforms
- Ensuring data integrity, accuracy, and consistency through rigorous quality checks and monitoring
- Expert in data quality, data validation and verification frameworks
- Innovate, explore and implement new tools and technologies to enhance efficient data processing
- Proactively identify and implement opportunities to automate tasks and develop reusable frameworks
- Work in an Agile and Scaled Agile (SAFe) environment, collaborating with cross-functional teams, product owners, and Scrum Masters to deliver incremental value
- Use JIRA, Confluence, and Agile DevOps tools to manage sprints, backlogs, and user stories
- Support continuous improvement, test automation, and DevOps practices in the data engineering lifecycle
- Collaborate and communicate effectively with the product teams, with cross-functional teams to understand business requirements and translate them into technical solutions
- Design, develop, and maintain complex ETL/ELT data pipelines in Databricks using PySpark, Scala, and SQL to process large-scale datasets
- Understand the biotech/pharma or related domains & build highly efficient data pipelines to migrate and deploy complex data across systems
- Design and Implement solutions to enable unified data access, governance, and interoperability across hybrid cloud environments
- Ingest and transform structured and unstructured data from databases (PostgreSQL, MySQL, SQL Server, MongoDB etc.), APIs, logs, event streams, images, pdf, and third-party platforms
- Ensuring data integrity, accuracy, and consistency through rigorous quality checks and monitoring
- Expert in data quality, data validation and verification frameworks
- Innovate, explore and implement new tools and technologies to enhance efficient data processing
- Proactively identify and implement opportunities to automate tasks and develop reusable frameworks
- Work in an Agile and Scaled Agile (SAFe) environment, collaborating with cross-functional teams, product owners, and Scrum Masters to deliver incremental value
- Use JIRA, Confluence, and Agile DevOps tools to manage sprints, backlogs, and user stories
- Support continuous improvement, test automation, and DevOps practices in the data engineering lifecycle
- Collaborate and communicate effectively with the product teams, with cross-functional teams to understand business requirements and translate them into technical solutions
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