Data Engineer-R&D Multi-Omics

*What you will do*

In this vital role you will be responsible for development and maintenance of software in support of target/biomarker discovery at Amgen.

• Design, develop, and implement data pipelines, ETL/ELT processes, and data integration solutions
• Contribute to data pipeline projects from inception to deployment, manage scope, timelines, and risks
• Contribute to 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 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 documentation of processes, systems, and solutions

*What we expect of you*

We are all different, yet we all use our unique contributions to serve patients. The role requires proficiency in scientific software development (e.g. Python, R, Rshiny, Plotly Dash, etc), and some knowledge of CI/CD processes and cloud computing technologies (e.g. AWS, Google Cloud, etc).

Basic Qualifications:

• Masters degree/Bachelors Degree and 5 to 9 years of Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field experience.

*Preferred Qualifications:*

• 5+ years of experience in designing and supporting biopharma scientific research data analytics (software platforms.

Functional Skills:

Must-Have Skills:

• Proficiency with 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 (or equivalent), 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:*

• Experience the git, CICD and the software development lifecycle
• Experience with SQL and relational databases (e.g PostgreSQL, MySQL, Oracle) or Databricks
• Experience with cloud computing platforms and infrastructure (AWS preferred)
• Experience using and adopting Agile Framework
• A passion for tackling complex challenges in drug discovery with technology and data
• Basic understanding of data modeling, data warehousing, and data integration concepts
• 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

*Professional Certifications:*

• Databricks Certified Data Engineer Professional preferred

*Soft Skills:*

• Excellent critical-thinking and problem-solving skills
• Strong communication and collaboration skills
• High degree of initiative and self-motivation.
• Demonstrated presentation skills
• Ability to manage multiple priorities successfully.
• Team-oriented with a focus on achieving team goals.