Data Engineer

Career Category Information Systems Job Description Join Amgen’s Mission of Serving Patients 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. 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. ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make 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 Data Engineer who can own the design & development of complex data pipelines, solutions and frameworks. The ideal candidate will be responsible to design, develop, and maintain 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 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 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 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: Data Engineering experience in Biotechnology or pharma industry 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 Minimum 5 to 8 years of 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. EQUAL OPPORTUNITY STATEMENT Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with 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 an accommodation. .