ABOUT THE ROLE

Role Description:

Amgen is seeking a Sr Data Engineer to design, develop, and support scalable enterprise data and integration solutions that enable analytics, reporting, and business decision-making. This role focuses on building and maintaining cloud-native data pipelines, APIs, and integration platforms using technologies such as Databricks, Apache Spark, MuleSoft, Airflow, and AWS.

The ideal candidate will have strong experience in big data processing, ETL/ELT development, API integration, workflow orchestration, and cloud data engineering practices. The successful candidate should possess strong problem-solving skills, a passion for data engineering, and the ability to work effectively in agile product delivery environments.

Roles Responsibilities:

- Design, develop, and maintain scalable data pipelines and cloud-native data solutions for data ingestion, transformation, processing, and distribution using Databricks, Apache Spark, Airflow, and AWS technologies.
- Design, build, and maintain MuleSoft APIs and integration solutions leveraging API-led connectivity and enterprise integration best practices to enable robust integrations between CRM and cross-functional enterprise systems.
- Develop and optimize ETL/ELT processes to support large-scale structured and unstructured data processing across multiple enterprise platforms.
- Participate in the end-to-end delivery of data engineering solutions including design, development, testing, deployment, monitoring, and operational support.

- Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs

- Build scalable and reusable data processing frameworks, components,



and integration services following enterprise engineering standards and best practices.
- Develop and maintain data models, metadata definitions, data dictionaries, and technical documentation to ensure data consistency, accuracy, and governance compliance.
- Implement data validation, reconciliation, and quality control processes to ensure reliability and integrity of enterprise data assets.

- Optimize Spark jobs, SQL queries, APIs, and ETL pipelines for scalability, reliability, and performance.
- Leverage AWS cloud services to develop scalable, resilient, and secure data solutions and integration services.
- Implement monitoring, logging, alerting, and operational support processes for data pipelines, APIs, and cloud-based integrations.
- Support CI/CD automation and DevOps best practices for data engineering and integration deployments.
- Identify, troubleshoot, and resolve complex data processing, integration, and performance-related issues in a timely manner.
- Research and evaluate emerging technologies, tools, and AI-assisted engineering capabilities that improve platform performance, developer productivity, and operational excellence.
- Adhere to software engineering best practices including coding standards, unit testing, reusable component design, peer reviews, and documentation standards.
- Participate in sprint planning, backlog refinement, estimation, and other agile software delivery activities.





Basic Qualifications and Experience:

- Masters / Bachelors degree and 9 to 12 years of Computer Science, IT or related field experience

Functional Skills:

Must-Have Skills

- Hands-on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing

- Proficiency in data analysis tools (eg. SQL) and experience with data visualization tools

- Skilled in MuleSoft API and Mulesoft integration job design and development

- Excellent problem-solving skills and the ability to work with large, complex datasets

- Strong understanding of data governance frameworks, tools, and best practices.

- Knowledge of data protection regulations and compliance requirements (e.g., GDPR, CCPA)

Good-to-Have Skills:

- Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development

- Robust understanding of data modeling, data warehousing, and data integration concepts

- Knowledge of AnyPoint Platform, Python/R, Databricks, SageMaker, Airflow, AWS cloud data platforms

- Proficiency in using Databricks Assistant, and other AI tools

Professional Certifications

- Certified in MuleSoft Certified Developer 1 or higher (preferred)

- Certified Associate or Professional Data Engineer / Data Analyst (preferred on Databrick)

- Certified AWS Professional or Associate certification (preferred)

Soft Skills:

- Excellent critical-thinking and problem-solving skills

- Strong communication and collaboration skills

- Demonstrated awareness of how to function in a team setting

- Demonstrated presentation skills

📌 Sr Data Engineer (Hyderabad)
🏢 Amgen
📍 Hyderabad