Data Quality Engineer - Remote

Martin’s Point Health Care•Portland, ME

3d•$99,963 - $123,484•Remote

About The Position

The Data Quality Engineer ensures the accuracy, reliability, and integrity of data used across Martin's Point Health Plan and Delivery Systems reporting environments. The role validates data, evaluates system outputs, and checks that analytics and operational processes meet defined standards. It provides objective quality oversight to cross-functional teams and helps ensure data-driven solutions function as intended, supporting consistent, transparent, and trustworthy decision-making. The position applies healthcare delivery system or health plan knowledge to assess operational, clinical, and regulatory expectations for data and reporting. It also contributes to continuous improvement through testing automation, data quality controls, and documentation, while maintaining records of test outcomes and quality findings to support transparency and audit readiness.

Requirements

Bachelor's degree in Information Systems, Computer Science, Data Analytics, Public Health, or a related field.
At least 4 years of experience in Quality Engineering, Data Quality, Software Testing, or a related role, including required experience validating data using SQL.
Experience writing complex SQL queries for data validation.
Experience working with healthcare delivery system or health plan data, such as claims, encounters, eligibility, provider, or clinical data.
Experience validating reports or dashboards in Power BI.
Understanding of data validation methodologies, testing principles, and QA best practices.
Knowledge of healthcare operational workflows, health plan processes, or clinical data environments.
Familiarity with ETL processes, data pipelines, and relational database concepts.
Awareness of data governance, data integrity standards, and regulatory considerations such as HIPAA.
Proficiency in SQL for data validation, profiling, and troubleshooting.
Ability to create structured test plans, test cases, and test documentation.
Skill in validating Power BI dashboards, datasets, and calculations.
Strong analytical and problem-solving skills and high attention to detail.
Effective communication skills for translating technical findings to non-technical stakeholders.
Ability to identify data anomalies, investigate root causes, and recommend corrective actions.
Ability to collaborate across technical, analytical, and business teams.
Ability to manage multiple priorities and deliver high-quality work with minimal or moderate supervision.
Ability to apply healthcare domain knowledge to ensure data accuracy and operational relevance.
Ability to adapt to evolving systems, tools, and organizational needs.
Must verify U.S. citizenship and complete required employment eligibility verification upon hire.

Nice To Haves

Experience using Power BI for report validation or data analysis.

Responsibilities

Validate inputs, outputs, and transformations across systems to ensure data accuracy and integrity for operational and reporting outcomes.
Develop test plans and test cases to ensure data processes meet business, regulatory, and operational requirements.
Execute functional, regression, and integration testing for data workflows, reporting solutions, and system enhancements.
Identify data anomalies, defects, and inconsistencies, and collaborate with technical and business teams to resolve them.
Design and execute SQL-based validation queries to assess data quality and support root-cause analysis.
Validate Power BI dashboards and reports for accuracy, consistency, and alignment with business definitions and data standards.
Apply healthcare delivery system or health plan knowledge to assess operational, clinical, and regulatory expectations for data and reporting.
Recommend and implement automated improvements to testing processes, data quality controls, and documentation practices.
Provide cross-functional teams with clear, objective quality insights to inform decisions and promote reliable data use.
Document testing outcomes, data validation results, and quality findings to support transparency and audit readiness.
Demonstrate the organization's mission, vision, and core values through consistent work.