Analytics Data Integration Developer-Associate- State Program Analytics-Hybrid

UPMC•Pittsburgh, PA

2d•Hybrid

About The Position

UPMC Health Plan has an exciting opportunity for an Analytics Data Integration Developer, Associate position in the State Programs Analytics department. This is a full-time position working Monday through Friday daylight hours and will be remote with the possibility of working in office. The Analytics Data Integration Developer, Associate creates and maintains programming, data set infrastructure, and other technical processes to integrate healthcare data elements from disparate sources throughout the UPMC enterprise. This integration results in a layer of information that fuels health economics activities including strategic analysis, predictive modeling, and clinical program evaluation.

Requirements

Bachelor's degree in information systems, data management, healthcare management, business, or related field.
Minimum of three years of work experience in information technology, healthcare, business, or research is required.
Experience and technical proficiency in SQL and/or SAS programming is required.
Experience with extraction and manipulation of large, complex data sets is required.
Experience managing/preparing data sets for use in analysis, modeling, or business operations is required.
Experience with Microsoft Office products (particularly Excel) is required.
Intermediate-level problem-solving skills are required.
The ability to effectively communicate issues and results, verbally and in writing, is required.
The ability to use effective time management skills, including prioritization of multiple tasks, is necessary for success.
Attention to detail is critically important in this role.
Ability to succeed in a fast paced, ambiguous/fluid environment.
A strong customer/stakeholder focus is expected at all times.
The successful Analytics Data Integration Developer, Associate, is a team player that displays professionalism at all times.
Ability to work extra hours if required.
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Nice To Haves

Master's or other advanced degree is preferred.
Experience in health insurance or Healthcare industry is preferred, but those with relevant experience in other industries may be considered.
Experience with other programming languages used in data science (such as R) is valuable.
Extensive experience in other programming languages may be considered.
Experience with data visualization tools (such as Tableau, QlikView, or PowerBI) is valuable.
Experience with geo-mapping software (such as ArcGIS) is valuable.

Responsibilities

Adopt and promote best practices, tools, and methods set by team/department leadership.
Maintain up-to-date information on status and effort related to each project.
Develop and maintain working relationships with internal UPMC health Plan departments, and external contacts as appropriate.
Meet deadlines and turnaround times set by supervisor. (These deadlines will, at times, require the employee to work until the project is completed, meaning extended daily work hours, extended work weeks, or both.)
Provide technical consultation and act as reference point to peers, other business areas, senior leadership and external customers.
Advise peers about existing programming that may be relevant to current/upcoming projects or requests.
Investigate data errors/variances and derive solutions with appropriate follow-up monitoring.
Optimize the searchability and indexing associated with the programming/technical content library.
Perform validation and ensure quality standards for data sets created by fellow team members.
Develop data extraction and integration processes to support analysis, data science, clinical operations, and decision support activities.
Maintain policies and procedures of the team/department.
Maintain a highly organized library of programming and other technical content used in data integration, analysis, and data science.
Make recommendations for optimal data extraction, manipulation, and integration methodologies based upon research and analysis.
Assist with orientation and process-specific training of new staff members.