2. Builds databases for data storage or processing and develop strategies for warehouse implementation, data acquisition, and archive recovery.
3. Optimizes data storage receptacles, manage ETL processes, and clean and maintain databases by removing and deleting old data.
4. Establishes physical database parameters.
5. Responsible for fulfilling BI requests not outsourced or manageable by power users.
6. Codes database descriptions and specify identifiers of database to database management system or direct others in coding database descriptions.
7. Specifies user access level for each segment of one or more data items such as insert, replace, retrieve, or delete data.
8. Specifies which users can access databases and what data can be accessed by user.
9. Evaluates new data sources for adherence to the organization's quality standards and ease of integration.
10. Tests and corrects errors, and refines changes to database.
11. Identifies, researches, and resolves technical problems as well as answer user questions.
12. Confers with co-workers to determine impact of database changes on other systems and staff cost for making changes to database.
13. Works with project and business leaders to identify analytical requirements.
14. Manages aspects of the warehouses such as data sourcing migration, quality, design and implementation.
15. Scopes, plans and prioritizes multiple projects.
16. Completes annual E-Learning Plan and Bank Secrecy Act (BSA) training as assigned and keeps up-to-date knowledge of BSA as it relates to the job function.
17. Performs other duties as assigned.
REQUIRED SKILLS & EXPERIENCE:
2. 5-7 years related experience in an IS/IT department managing databases, warehouses and/or secondary repositories, data mining (using Joins, matching, etc.) within said receptacle(s) to extract pertinent records related to query requests, and effectively building, maintaining and trouble-shooting ETL procedures.
3. Experience with SQL, MS SQL Service and MS Access.
4. Familiar with field’s concepts, practices and procedures.
5. Familiar with Data Quality procedures and processes
6. Familiar with Metadata and Data Dictionary procedures and processes
7. Understands the Advanced Analytics concepts such as Clustering, Association, and/or Data Mining
8. Ability to document procedures and build work instructions.
9. High attention to detail.
10. High level of independence and responsibility for own actions.
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