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Data Quality Analyst II

Sparksoft CorporationRemote/Hybrid if local to MarylandPosted 5 Nov 2026

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About this role

Join us at Sparksoft, where we're not just another tech company—we're a catalyst for change. Our mission isn't just to offer IT solutions; it's to revolutionize the way you work. Here, passion isn't just a buzzword; it's the fuel behind groundbreaking ideas and transformative technologies. We serve a wide range of government clients, delivering impact that's felt across the nation. Our true strength lies in our people.

They're the problem-solvers and innovators consistently delivering extraordinary outcomes. With Sparksoft, you're not stepping into a routine job; you're joining a team committed to innovation and excellence. Our innovation extends beyond just delivering projects. Through our specialized Innovation Centers, we continuously refine our methods, ensuring we remain industry leaders. We are Sparksoft! ROLE & RESPONSIBILITIES: The Data Quality Analyst II drives continuous improvement in program data quality by developing solutions and strategies that address business challenges.

Working closely with data operations and reporting teams, this role designs, develops, and executes automated reporting solutions that meet high standards for quality and performance. The position requires strong technical expertise, excellent problem-solving skills, and effective collaboration in a SAFe Agile environment. The analyst plays a critical role in improving the quality and accessibility of data solutions that support the Centers for Medicare & Medicaid Services (CMS) in detecting and preventing fraud, waste, and abuse in government-sponsored health programs Analyze structured and unstructured data from multiple sources to identify errors and inconsistencies, correct data issues, and implement processes that improve data accuracy, completeness, and reliability.

Ensure the accuracy, completeness, and reliability of APS data. Work with a range of data types, including structured and unstructured data, and use a variety of tools and techniques to analyze and improve data quality. Use tools and techniques such as statistical analysis, data cleansing and transformation tools, and data governance frameworks. Develop and implement data quality policies, procedures, and standards. Document processes, prepare reports, and make recommendations for process improvements.

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Develop new processes and procedures to enhance operations. Collaborate with other teams to implement changes or updates in the existing reports. Advanced Excel expertise required including use of pivot tables, formulas, conditional formatting, etc. Present responses and findings to business owners, customers, leadership. Provide support in ad-hoc analysis to meet customer needs. Perform statistical tests on large datasets to assess data quality and integrity.

Collaborate with internal team to improve data collection and storage processes. Analyze and identify data quality issues, develop methods to address data quality problems. Advanced Excel expertise required including use of pivot tables, formulas, conditional formatting, etc. Review and understand artifacts related to data ingestion and transformation as it applies to data validation and analysis. Provide quality assurance reports using tools like Excel, SharePoint, Power BI, and Tableau.

Streamline internal processes and strengthen organizational support using Excel, SharePoint, Power BI, and Tableau. Performs ad hoc data analysis to support programmatic questions and stakeholder requests. Works as part of a project team to determine project requirements, goals, implementation, and schedules. Develop scripts and dashboards to monitor the accuracy and quality of data flow. Maintain data accuracy and quality checks by monitoring/reviewing the dashboards and reports regularly.

Provide training for internal users and customer stakeholders. Provide technical leadership within the data analytics team and mentor junior team members. Peer review of team members’ work outputs for quality assurance. Experience with data analytics tools (SQL, R, Python) and data visualization tools (like Tableau, PowerBI, AWS Quicksight). Knowledge of databases (PostgreSQL, Oracle) and data modeling. Assess/evaluate to deliver timely data reporting, and data solutions against client requirements.

Ensure customer satisfaction through follow-up, client responsiveness, and thorough communication. Ability to manage multiple clients and projects/tasks simultaneously. Participate in Agile ceremonies, such as sprint planning, daily stand-ups, and retrospectives, to provide input on testing progress and challenges. Technical Competencie

Source listing: greenhouse_sparksoftcorporation

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