Enterprise Architect

experience:

5.1. Master’s degree in Computer Science, Analytics/Data Science, Information Systems, or

another related field. Equivalent work experience may be substituted for the educational

requirements at a rate of one year of experience for one year of education.

5.2. Five years of experience interfacing directly with various lines of business; must

demonstrate an understanding of general business operations, preferably in healthcare

related fields.

5.3. Eight years of experience in Data Warehouse and Data Lake architecture, design, and

development.

5.4. Ten years of experience in data architecture data modeling (including Entity

Relationship, Logical, Conceptual, and Physical models), and data profiling/reverse

engineering in both schema-on-read and schema-on-write environments. The

experience includes proficiency with standard modeling tools like Erwin.

5.5. Ten years of experience with Data Pipeline tools, including design, performance

optimization and development/engineering, for both batch (i.e., ETL) and streaming (i.e.,

Kafka) capabilities.

5.6. One year of experience with Data Mesh and/or Data Fabric architecture design and/or

implementation.

5.7. Ten years of experience with SQL programming inclusive of stored procedures, functions,

and triggers.

5.8. Five years of experience with Python or similar object-oriented high-level programming

language.

5.9. Ten years of experience with relational and No SQL (Document, Graph, Key-Value)

databases.

5.10. Ten years of experience implementing cloud architecture patterns in cloud platforms like

Azure or AWS, including ingress/egress, security considerations and storage/processing

cost optimization.

5.11. Five years of experience designing technology solutions using composable architecture

and microservices.

5.12. Five years of experience designing data hubs via a canonical data model, as well as

governing, incorporating the use of, and optimizing APIs for data exchanges.

5.13. Five years of experience with source control systems such as Azure DevOps.

5.14. Two years of experience utilizing Dev or DataOps processes.

5.15. Five years of experience in data testing/QA best practices (including performance), tools

and automation.

5.16. Five years of experience architecting and implementing Data Governance related

solutions such as Master Data Management, Data Quality, Data Catalog and Metadata

Management.

5.17. Ten years of experience architecting and implementing Business Intelligence tools.

5.18. Five years of experience architecting and implementing Advanced Analytics platforms,

including model life-cycle management and machine learning.

5.19. Two years of experience designing solutions augmented with artificial intelligence.

5.20. Five years of experience working with large volumes of data in the petabyte range.