COMPANY OVERVIEW

With an annual budget of $2.3 billion and more than 7,000 employees throughout the five boroughs, the New York City Department of Health and Mental Hygiene (NYC DOHMH) is one of the largest public health agencies in the world, serving 8 million New Yorkers from diverse ethnic and cultural backgrounds. We’re tackling a broad range of public health issues with innovative policies and programs and getting exceptional results, but our work is never finished. The breadth of our innovative programs provides the widest range of choices for every member of our team.
With grant funds from the Centers for Disease Control and Prevention (CDC), DOHMH is undertaking a new initiative that will meet critical infrastructure needs and make possible strategic investments that will have lasting effects on public health. Investments and improvements through this initiative will help modernize DOHMH’s foundational capabilities and data infrastructure, enabling it to partner in complex health and health care environments and, in turn, support better public health outcomes, including COVID-19. This initiative supports larger efforts to rebalance investments in public health and more equitably serve communities and populations.
The selected candidate will be an employee of Public Health Solutions, a nonprofit organization which is the fiscal and administrative manager of the grant but will work be supervised by DOHMH. This is a grant-funded position ending in November 2027. This position will be based at the Health Department’s office in Long Island City, NY, with the possibility of hybrid work.

PROGRAM DESCRIPTION

This position will be within the Health Department’s innovative Center for Population Health Data Science (CPHDS). CPHDS is working to strengthen citywide population health surveillance by better linking public health, healthcare, and social service data to fully characterize and improve the health of New Yorkers. Our vision is for these data to be accessible, timely, equitable, meaningfully usable, and protected – and being actively to protect and promote health and wellbeing of New Yorkers.

JOB DESCRIPTION

As a QA Engineer, you will be responsible for testing and validating our data pipelines to ensure high-quality data is processed and delivered. You will work closely with Data Engineers, Data Analysts, and other stakeholders to verify the integrity, performance, and functionality of data processing systems from ingestion to transformation and storage.
This position will be based at the Health Department’s office in Long Island City, NY, with the possibility of hybrid work.

QUALIFICATIONS:

• Bachelor’s degree in Computer Science, Information technology, Engineering, or a related (or equivalent experience).
• At least 3 years of experience that is highly relevant to responsibilities above.

• Test Data Pipelines: Develop and execute comprehensive test plans to ensure the reliability and accuracy of data pipelines, including data extraction, transformation, and loading (ETL) processes.
• Test Services: Develop and execute comprehensive test plans to ensure the reliability and accuracy of services and service-oriented workflows.
• Automation Testing: Create and maintain automated tests for data pipelines and integrate them into CI/CD workflows to ensure data quality and pipeline stability.
• Data Validation: Validate the integrity, consistency, and accuracy of data processed through various pipelines by comparing raw data to processed data.
• Performance Testing: Monitor and test pipeline performance, identifying bottlenecks or inefficiencies and working with engineers to resolve them.
• Debug and Troubleshoot: Investigate and troubleshoot issues within data pipelines, working with cross-functional teams to resolve discrepancies or failures in the data flow.
• Test Documentation: Document test results, maintain test scripts, and provide detailed reports on issues found during testing.
• Collaboration: Work closely with Data Engineers to design and improve testing strategies, ensuring all data quality issues are addressed proactively.
• Continuous Improvement: Actively contribute to refining testing processes, methodologies, and automation practices to enhance the quality of the data pipelines.
• Regression Testing: Perform regression testing of data pipelines after code changes or new feature deployments to ensure the system remains stable.