Data Analyst

16dacedb-7a98-4245-99e5-71caf71992fa•Kaneohe, HI
•$0 - $35•Onsite

About The Position

ATA Services, Inc. is seeking a full-time Data Analyst to support its client, Hawaii State Hospital. This long-term position is located at Hawaii State Hospital, 45-710 Kea’ahala Road, Kaneohe, HI 96744-3597. The position is non-exempt and pays $34.72 per hour. The Data Analyst identifies and resolves data inconsistencies and discrepancies. The role also facilitates an advisory or steering committee of data users to identify modifications needed to improve data-system functionality.

Requirements

  • Bachelor’s degree from an accredited four-year college or university.
  • At least two and one-half years of progressively responsible professional work experience requiring a high degree of analytical skill.
  • Experience using large, complex relational databases to gather, evaluate, and analyze facts and other relevant information to resolve problems and/or determine and recommend appropriate courses of action.
  • Knowledge of security and confidentiality policies and procedures, including procedures for maintaining confidentiality and securing electronic data.
  • Knowledge of principles, practices, methods, and techniques related to program planning, development, monitoring, and evaluation.
  • Proficiency with large, complex relational databases; ability to develop, design, and manage multiple databases.
  • Ability to understand and complete complex oral and written instructions; write clearly and in an organized manner; think critically; solve problems; plan, coordinate, and work on projects with others; implement data-management quality control and assurance procedures; and interact professionally.

Nice To Haves

  • Experience with Power BI.

Responsibilities

  • Identify and resolve data inconsistencies and discrepancies.
  • Facilitate an advisory or steering committee of data users to identify modifications needed to improve data-system functionality.
  • Use and manage relational databases for program implementation, monitoring, and evaluation.
  • Apply data-management quality control and assurance procedures.
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