Sr Data Engineer – Research Data and Analytics

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: 

In this role, you will design, build and maintain data lake solutions for scientific data that drive business decisions for Research. You will build scalable and high-performance data engineering solutions for large scientific datasets and collaborate with Research stakeholders. The ideal candidate possesses experience in the pharmaceutical or biotech industry, demonstrates strong technical skills, is proficient with big data technologies, and has a deep understanding of data architecture and ETL processes. 

Roles & Responsibilities:  

• Design, develop, and implement data pipelines, ETL/ELT processes, and data integration solutions 

• Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks 

• Develop and maintain data models for biopharma scientific data, data dictionaries, and other documentation to ensure data accuracy and consistency 

• Optimize large datasets for query performance 

• Collaborate with global cross-functional teams including research scientists to understand data requirements and design solutions that meet business needs 

• Implement data security and privacy measures to protect sensitive data 

• Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions 

• Collaborate with Data Architects, Business SMEs, Software Engineers and Data Scientists to design and develop end-to-end data pipelines to meet fast paced business needs across geographic regions 

• Identify and resolve [complex] data-related challenges 

• Adhere to best practices for coding, testing, and designing reusable code/component 

• Explore new tools and technologies that will help to improve ETL platform performance 

• Participate in sprint planning meetings and provide estimations on technical implementation 

• Maintain comprehensive documentation of processes, systems, and solutions 

Basic Qualifications and Experience: 

• Doctorate Degree OR 

• Master’s degree with 4 - 6 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field OR  

• Bachelor’s degree with 6 - 8 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field OR 

• Diploma with 10 - 12 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field  

Preferred Qualifications and Experience: 

• 3+ years of experience in implementing and supporting biopharma scientific research data analytics (software platforms) 

Functional Skills: 

Must-Have Skills: 

• Proficiency in SQL and Python for data engineering, test automation frameworks (pytest), and scripting tasks 

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

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

Good-to-Have Skills: 

• A passion for tackling complex challenges in drug discovery with technology and data 

• Strong understanding of data modeling, data warehousing, and data integration concepts 

• Strong experience using RDBMS (e.g. Oracle, MySQL, SQL server, PostgreSQL) 

• Knowledge of cloud data platforms (AWS preferred) 

• Experience with data visualization tools (e.g. Dash, Plotly, Spotfire) 

• Experience with diagramming and collaboration tools such as Miro, Lucidchart or similar tools for process mapping and brainstorming 

• Experience writing and maintaining technical documentation in Confluence 

• Understanding of data governance frameworks, tools, and best practices 

Professional Certifications: 

• Databricks Certified Data Engineer Professional 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