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.
Any Graduates