Personify Health · 4 days ago

Healthcare Lead Data QA Analyst

United States

Full-time

Remote

Senior Level

$90K/yr - $100K/yr

6+ years exp

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ConsultingElectronic Health Record (EHR)

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Responsibilities

Assist in the development, maintenance, and implementation of QA testing plans, methodologies, toolsets and mindsets.

Understand testing and quality goals by translating requirements from internal business partners and client goals.

Report and triage defects and incidents. Understand and participate in RCA reporting and socialize ‘lessons learned’ and best practices within the QA and engineering teams.

Perform ad-hoc and automated QA tasks.

Participate in, and contribute to planning for any data processing pipeline enhancements

Help monitor, maintain, and improve errors of our data pipelines.

Communicate with and educate other non-data teams to ensure clear communication and a proactive approach toward accurate translation of client requirements into the corresponding data transformations.

Create and maintain documentation of QA processes, tools, and environments.

Supervisory responsibilities for 1-3 individuals.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

QA for medical claims dataData QA experienceSQLTesting automationHealthcare software QAData transport methodsExcel proficiencyIT related certificationMentoring QA analystsGit experience

Required

3+ years of experience handling QA for medical claims related data

6+ years of hands-on data QA Experience

3-5 years experience with SQL

1-2 years of experience directly leading and mentoring junior QA analysts or engineers

SW certification or degree in IT related field

Experience writing, understanding, and maintaining testing automation or reporting in multiple software languages

Hands-on QA Experience with Healthcare software, data, and data transformations. This should be within claims processing in multiple systems including legacy systems.

Strong practical understanding of multiple data Transport methods and data parsing.

Demonstrated ability to interact with 3rd parties or vendors related to data processing pipelines

Proficient in the use of Excel and other analytical tools

Detail oriented and able to examine data and code for quality and accuracy.

Self-Starter – taking initiative when inefficiencies or opportunities are seen.