The Lead Data Architect works in all data environments which includes data design, database architecture, metadata and repository creation. The Lead Data Architect works on problems of diverse scope and complexity ranging from moderate to substantial.Responsibilities
The Lead Data Architect responsible for developing blueprints for all data repositories, evaluating hardware and software platforms, and integrating systems. Translates business needs into long-term data architecture solutions. Defines, designs and builds dimensional database schemas. Evaluates reusability of current data for separate analyses. Conducts data sheering to rid the system of old, unused or duplicate data. Reviews object and data models and the metadata repository to structure the data for better management and quicker access. Advises executives to develop functional strategies (often segment specific) on matters of significance. Exercises independent judgment and decision making on complex issues regarding job duties and related tasks, and works under minimal supervision, Uses independent judgment requiring analysis of variable factors and determining the best course of action.
For the Enterprise Clinical Operating Model, we will be moving Humana's clinical programs to a cloud native, SaaS-based workflow platform - the Lead Data Architect will work on data design within that platform, as well as on dashboarding andETLs from that platform (or real-time data movements) to other systems and for reporting purposes. Experience working with vendor data models as well as both relational and non-relational data stores is highly preferred.Required Qualifications
- Bachelor's Degree in Computer Science, Information Technology or related field
- Operational Data Integration for real-time APIs
- Big Data Integration & Analytics
- Must be passionate about contributing to an organization focused on continuously improving consumer experiences
Additional InformationScheduled Weekly Hours
- Master's Degree
- Experience working with cloud-based data stores and data integrations, as well as vendor data models and both relational and non-relational data stores.