Data Engineer
Amgen
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This role on the market
9,420 open data roles across 953 companies are on ApplySarthi right now, most of them in Bengaluru (509), Hyderabad (334), Mumbai (159).
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What data roles keep asking for: Python (38%), SQL (33%), AWS (30%), Machine learning (19%), Spark (15%), Databricks (14%), Stakeholder management (13%), Azure (13%) — counted across their open postings here.
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Amgen has 1,937 open roles listed here.
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Counted across 14 company job boards, updated as roles open and close.
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Questions you are likely to be asked
- Why do you want to join Amgen?
- What is your experience with Agile? Tell me one thing you learned the hard way.
- What would you check first if a model's accuracy dropped after going live?
- When would you not use machine learning for a problem?
- Walk me through a model you built, from the data to how it was used.
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Practise the Data Engineer at Amgen interview free →Career Category Manufacturing Job Description Role Description: Let’s do this. Let’s change the world. We are looking for a highly motivated expert Data Engineer to design and develop advanced data pipelines and solutions for our Manufacturing Applications Product Team. The ideal candidate will be responsible for designing, developing, and optimizing data pipelines, data integration frameworks, and metadata-driven architectures that enable seamless data access and analytics for Manufacturing and Operations use cases. This role requires 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. Build highly efficient data pipelines to migrate and deploy complex data across systems, with an understanding of biotech/pharma/manufacturing or related domains. 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, PDFs, and third-party platforms. Ensure data integrity, accuracy, and consistency through rigorous quality checks and monitoring. 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 product teams and 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 and 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. Experience with streaming technologies such as Apache Kafka, Debezium, or similar platforms for real-time data processing and integration. Good-to-Have Skills Experience with AI assisted code development using tools like GitHub Copilot, Cursor, Claude Code. Data engineering experience in biotechnology or pharma industry. Experience in writing APIs to make data available to consumers. Experience with SQL/NoSQL databases, vector databases for large language models. Experience with data modeling and performance tuning for both OLAP and OLTP databases. Experience with software engineering best practices, including version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven, etc.), automated unit testing, and DevOps. Experience with manufacturing related data sources like SCADA, Data Historians is a plus Education and Professional Certifications • Master’s /Bachelor’s degree and 5-8 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. .
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Listed on workday · posted 2026-10-12. ApplySarthi collects openings and links to application pages; the role is advertised by Amgen, not by us.