The Data Services team at Patterson Dental specializes in crafting sophisticated data strategies, architecting robust data models, and enabling innovative self-service and data-driven capabilities. Our focus extends to upholding the highest standards of data quality and governance. We play a pivotal role in designing, developing, testing, and deploying large-scale data warehouse solutions and other data services that power Patterson’s leading SaaS products in the dental services market. The Data Quality Engineer is a key role within the Data Services team and is focused on creating, implementing, and monitoring metrics and systems designed to ensure continuous data quality and integrity — backbones to the value of our future data products and services. Essential Functions Develop and implement data quality standards and processes: Work closely with data engineers to ensure that data sources, data processing, and data storage adhere to established quality metrics and standards. Monitor data quality: Regularly review data through automated and manual tests to detect and correct quality issues. Identify, analyze, and interpret trends or patterns in complex data sets. Data Quality Metrics: Design and develop systems and reports to monitor and report on data quality. Make recommendations for improvement based on findings. Collaboration: Coordinate with IT, data governance, and data engineering teams to implement improvements in data quality within business processes. Tool Development: Build and maintain automated data quality testing tools to facilitate continuous quality checks. Documentation: Maintain clear and concise documentation that outlines processes, anomalies, resolutions, and quality standards. Required Qualifications Educational Background: Bachelor’s degree in Computer Science, Data Science, Information Management, or a related field. Experience: Minimum of 3 years of experience in a data quality role, preferably within a healthcare-related SaaS environment. Technical Proficiency: Strong understanding of SQL and data management tools (e.g., Azure Data Factory, SQL Server, Cosmos DB). Experience with Python or R for data analysis and quality checks is a plus. Knowledge in Data Governance: Experience with data governance practices and understanding of regulatory standards like HIPAA and CCPA. Analytical Skills: Excellent problem-solving skills and the ability to analyze complex data systems and extract insights related to data quality. Communication and Collaboration: Strong interpersonal skills with the ability to work effectively across multiple teams and communicate findings and recommendations clearly to both technical and non-technical stakeholders. Experience with Agile and DevOps: Familiarity with agile methodologies and the application of DevOps principles to data management practices. Desirable Skills Certifications: Certifications in data quality, data governance, or related fields are highly advantageous. Project Management: Skills in managing projects involving multiple stakeholders and complex requirements. Working Environment Office environment – either in Patterson facility or at home/remote location Travel to corporate sites is periodically required (Quarterly or so) Periodic on call rotations and available outside of normal business hours on evenings and weekends during critical production release or issue escalation periods This role is eligible for hire in any of the following States: AK, AZ, CA, CO, CT, DC, HI, ID, IL, KS, KY, ME, MA, MI, MN, MT, NE, NV, NH, NM, NY, OR, RI, SD, TX, UT, VT, WA, WV, WI The potential compensation range for this role is below. The final offer amount could exceed this range, based on various factors such as candidate location (geographical labor market), experience, and skills. $85,000 – $105,000
azure-cosmosdb data-quality Azure Data Factory Agile Data Analyst Analytical skills data-warehouse Python data-driven Data Storage HIPAA R Microsoft SQL Server SaaS Communication DevOps data-modeling data governance Collaboration SQL dataservice ccpa data-processing Project management