Overview
Position : Insights Architect
Location : Hartford, CT
Informatics Capabilities (Practical Knowledge of) Required
- Audit and Reconciliation processes
- Data Lineage concepts (code traceability)
- Data Quality best practices and techniques
- Data Warehouse and DataMart environments
- Complex history generation and storage
- Application architectural componentization and rationalization techniques and process
- Architecture principles and best practices
- UML component modeling and design processes and best practices
- The delineation between architecture and high level design
- NoSQL environments including tools
- Meta data and the use of it by applications
- Semantic data, technology, and solutions
- Very large database environments
- Big data environments and architecture including tools
- Leadership of large and varied technical teams
- Information Delivery and Business Intelligence application design
- Data Analytics and Measures Data Enrichment Processing
- Data Mining techniques for Insights using verified business facts
- Business user classifications (ie. Adhoc, Novice, and Power Users)
- Healthcare and Insurance Services industry knowledge
- Complex source-to-target mapping rules and techniques
- Data modeling of relational and dimensional databases
- Multi-dimensional environments and modeling
- Application modeling tool expertise (IDA, RSA respectively)
Data Science Capabilities (Practical Knowledge) Required
- Data Discovery and Exploration techniques and processes
- Data Mining techniques for Insights using a wide set of source data
- Determining the nature and usability of certain data
- Techniques to apply data analysis for Business Requirements creation
- Sand-Box environments and best practices
- Structured, Unstructured, Semi-Structured Data techniques and processes
Experience Required
Candidate should have a minimum of 15 years of demonstrable architecture experience in a large organization. The experience should contain at least 10 years of architecture support combined of these environments: warehouse, datamart, business intelligence, and big data.