Senior Data Architect

4 days ago


North Chicago Illinois, United States AbbVie Full time
About the Role

We are seeking a highly skilled Senior Data Architect to join our Bioinformatics Engineering team at AbbVie's Genomics Research Center (GRC). The successful candidate will play a key role in developing scalable data storage and management solutions to maximize the value of our data.

Key Responsibilities
  • Design and Develop Omics Data Storage Platforms: Design and develop efficient and scalable omics data storage platforms to accommodate large-scale bioinformatics data.
  • Collaborate with Bioinformatics Engineers and Scientists: Collaborate with bioinformatics engineers and scientists to understand data requirements and develop loading processes for newly generated omics data.
  • Build Robust APIs for Data Access and Integration: Build robust and secure APIs to facilitate data access, retrieval, and integration across different bioinformatics applications.
  • Optimize Data Storage and Retrieval Operations: Optimize the performance of data storage and retrieval operations to ensure quick and accurate access to omics data.
  • Implement Data Governance and Security Measures: Implement data governance and security measures to maintain data integrity and assure stakeholder access.
  • Stay Up-to-Date with Emerging Technologies: Stay up-to-date with emerging technologies and industry trends in bioinformatics and data architecture to drive innovation and improve data management processes.
  • Provide Technical Leadership and Guidance: Provide technical leadership and guidance to junior data architects and developers in the team.
  • Collaborate with Other Bioinformatics Engineering Sub Teams: Collaborate with other Bioinformatics Engineering sub teams to identify and address data integration and interoperability challenges.
  • Conduct Performance Analysis and Troubleshooting: Conduct performance analysis and troubleshooting to identify bottlenecks and implement solutions for improved system performance.
  • Collaborate with Data Scientists and Analysts: Collaborate with data scientists and analysts to develop data models and structures that enable effective data analysis and interpretation.


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