Technical Data Analyst III

GHX

10h•$81,000 - $108,000•Remote

About The Position

Reporting to the Supervisor, SW Engineering, the Data Analyst III, is responsible for analyzing, reporting and enriching platform data. As part of the Common Data Platform Team, your work will enable capabilities for GHX’s data and analytics solutions utilized by hospitals and suppliers. This role is responsible for independently analyzing, debugging, documenting, and modifying data to ensure high quality data for the consumers.

Requirements

Bachelor’s degree in computer science, or relevant discipline
5-8 years of professional work experience analyzing and finding insights in large data sets
Experience with the Snowflake database platform and reporting tools such as Power BI, Tableau and Sigma
Proven analytic skills, including mining, evaluation, analysis, and visualization
Ability to learn rapidly and adapt quickly to changing situations.
Strong attention to detail and a proactive problem-solving attitude.

Nice To Haves

Familiarity with data science tools, like python or R, is a plus.
Familiarity with healthcare data rules and standards (such as HIPAA) from working with health or healthcare data (healthcare supplies procurement, purchasing, logistics, or data from EHR/EMR systems like Epic or Cerner) is a plus.
Supply chain or Heathcare background is a plus.

Responsibilities

Identify patterns and relationships to evaluate, maintain and enrich data quality across multiple systems and data sources
Continually assess and evaluate processes to improve efficiency in data cleansing activities, with a focus on identifying automation opportunities.
Develop flexible, reusable, and efficient SQL code while adhering to best practices.
Conduct root cause analysis (RCA) and impact analysis to identify data quality issues, inform automation efforts, and report findings to teams and stakeholders
Optimize queries and procedures, troubleshoot and resolve issues, and collaborate with team members to analyze business requirements
Contribute to the design and implementation of ETL processes using PL/SQL, SQL or Python.