Develop strategies for data acquisitions, management, governance, use, and retention of data assets; provides thought leadership in improving data quality and develops specific metrics for quality reviews of data.
This position will serve as the primary advisor to the company's Healthcare Analytics leadership with respect to architecture, technology, configuration, and scale-out decisions pertaining to the Insight Generation BI environment.
Demonstrate technical expertise, establishes credibility with both technical resources and decision makers. Work with client systems, performance, and current and potential data loaded onto systems to facilitate demand creation.
Ideally you will carry experience implementing Big data ecosystems in a cloud environment designing AWS data lake environment with data ingestion and integration working with DynamoDB, EMR, EC2 and Amazon Redshift.
Design all of the components of the system including, datastores, connection points between systems (i.e. Relativity, Lease Enabler, Model execution environment and the MVP environment) and other components needed for the MVP
The Senior Enterprise Data Architect will lead an agile team to build out new cloud architecture, positioning Client for a future state in which the company triples in size, and in which data science and analytics teams spearhead data-driven strategy across all company verticals and platforms.
This individual will provide DBMS expertise to application teams during incident resolution, be a point of escalation for on-call resources, and work to proactively deliver best-in-class availability across companys database platforms.
The Oracle DBA must provide hands on technical expertise, knowledge and feedback on complex projects including, but not limited to, complex database installations, data migration and database performance tuning, ensuring a successful integration and communication among several operational systems, databases and applications.
Manipulating, aggregating and deriving useful information from data stored across many sources and different databases; using and defining automated tests to verify that loads and transformations work as intended.