Amgen is looking for highly motivated expert Senior Data Engineer who can own the design & development of complex data pipelines, solutions and frameworks. The ideal candidate will be responsible for designing, 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 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 data pipelines using AWS (Redshift, S3, Glue, Lambda) and Databricks (Spark, Delta Lake) to support enterprise analytics and reporting
Architect and implement robust data models (dimensional and normalized) to enable high-performance querying and optimized reporting in Redshift
Build and optimize batch and real-time data processing frameworks, leveraging Spark Structured Streaming and cloud-native services
Lead data ingestion, transformation, and orchestration workflows ensuring data quality, reliability, and performance at scale
Perform advanced data analytics and root cause analysis to troubleshoot data discrepancies, performance issues, and pipeline failures
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 and drive continuous improvements in CI/CD pipelines for automated data pipeline deployments, automated testing, version control, and monitoring for data platforms in a cloud-native environment
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
Partner with BI and reporting teams to support report development, dashboard optimization, and data validation for business stakeholders
Implement data governance best practices including data lineage, auditing, access controls, and performance tuning
Mentor junior engineers and contribute to architectural decisions, code reviews, and engineering standards
Basic Qualifications and Experience:
Any degree with 8 - 13 years of experience in Computer Science, IT or related field
Functional Skills:
Must-Have Skills:
Strong solution design and problem solving skills
Hands-on experience in data engineering technologies such as Databricks, PySpark, SparkSQL Apache Spark, AWS, Python, SQL, Redshift, 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 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
8 to 13 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