Job Title: Data QA Analyst
Location: Quincy, MA 02171 (Hybrid)
Hire Type: Contract (12 months)
POSITION DESCRIPTION:
***Only qualified Data QA Analyst candidates located in the Quincy, MA area will be considered due to the position requiring an on-site presence***
Required Education:
- Undergraduate degree in a STEM discipline, Business, Computer Science, Public Health, related field, or equivalent experience.
Preferred Certification:
Required Skills and Experience:
- Effective and good communications skills
- Ability to work with teams and independently
- Experience with state or local public health data systems (e.g., disease surveillance, immunization registries, ELR, syndromic surveillance, vital records)
- Familiarity with state data standards (e.g., HL7)
- Knowledge of HIPAA, state privacy laws, and data use agreements
- Familiarity with analytic tools such as R, Python, or SAS; and reporting/visualization tools such as Tableau or Power BI
- Experience in creating, reviewing and maintaining end-to-end data platform requirements
- Thorough knowledge and experience of data warehouse and a cloud-based Enterprise Data solution
- Cloud database platform experience such as Snowflake
- Familiarity with AWS cloud services
- Intermediate or better SQL query skills
- Working knowledge with at least one Business Intelligence tool such as Tableau.
Preferred Skills and Experience:
- Public Health experience
- Amazon Web Services experience
- Tableau reporting experience
Client is looking for a highly skilled and experienced candidate to fill the Senior Data Quality Assurance Analyst position for Data Modernization Initiative (DMI) Projects. Client is executing large-scale data modernization across the agency as part of DMI. This includes creating a consolidated Enterprise Data Platform on modern cloud tools (including AWS & Snowflake) and re-platforming existing business data applications from solutions such as SAS and legacy databases to the new platform. Client s data systems enable epidemiologists, public health researchers, state and local public health officials, and business leaders to analyze public health trends and drive policy decisions.
The ideal candidate is an expert in assuring accuracy, completeness, timeliness, and consistency of data used by the State Department of Health to support disease surveillance, population health monitoring, program evaluation, and statutory reporting. This position works collaboratively with epidemiologists, program staff, analytics teams, developers, and external partners to maintain data integrity across state public health information systems and reporting processes.
In this role, you are comfortable speaking to both business and technical stakeholders to ensure combined understanding and collaborative solutions. This role will be expected to own tasks and follow-up related to cloud data platform requirements and implementation activities and establish well documented best practices and processes.
Duties and Responsibilities:
- Develop, implement, and maintain data quality standards, validation rules, and monitoring procedures for state public health datasets
- Implement EDP quality checks and validation procedures as informed by Epidemiologists/data stewards
- Monitor key data quality dimensions including accuracy, completeness, consistency, timeliness, and validity
- Identify, document, track, and support resolution of data quality issues affecting the METRIK project and the various Data Assets needed to power public health analytic use-cases
- Establish and perform processes to monitor technical integrity of data pipelines
- Partner with epidemiologists, program managers, data stewards, and developers to assess the impact of data quality issues on analysis, reporting, and program outcomes
- Validate data at various steps in the data ingestion process from staging to curation to making data available to analytics
- Support development and maintenance of data dictionaries, metadata, and business rule
- Participate in data governance and stewardship activities, including data access controls, data lineage, and standardization efforts
- Support system enhancements, onboarding of new data sources, and policy-driven data changes with quality assurance testing.
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