Senior IT Analyst - Data Quality & Excellence

The US Oncology Network•Rowlett, TX

16d•Remote

About The Position

The US Oncology Network is looking for a Remote Senior Healthcare IT Analyst - Data Quality & Excellence to join our team. Some travel may be necessary, up to 25%. Must currently reside in Texas. As a part of The US Oncology Network, Texas Oncology delivers high-quality, evidence-based care to patients close to home. Texas Oncology is the largest community oncology provider in the country and has approximately 600+ providers in 300+ sites across Texas, our founders pioneered community-based cancer care because they believed in making the best available cancer care accessible to all communities, allowing people to fight cancer at home with the critical support of family and friends nearby. Our mission is still the same today—at Texas Oncology, we use leading-edge technology and research to deliver high-quality, evidence-based cancer care to help our patients achieve “More breakthroughs. More victories.” ® in their fight against cancer. Today, Texas Oncology treats half of all Texans diagnosed with cancer on an annual basis. The US Oncology Network is one of the nation’s largest networks of community-based oncology physicians dedicated to advancing cancer care in America. The US Oncology Network is supported by McKesson Corporation focused on empowering a vibrant and sustainable community patient care delivery system to advance the science, technology, and quality of care.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Data Science, Business, Healthcare Administration, Finance, or a related field preferred.
Associate’s Degree + four (4) years of related work experience
High School diploma or equivalent and eight (8) years of related work experience
Minimum five (5) years of experience in data analytics, data governance, master data management, business intelligence, or related disciplines.
Experience managing and analyzing large datasets and relational databases.
Experience identifying and resolving complex data quality and data integrity issues.
Experience leading cross-functional initiatives, projects, and collaborating with both business and technical stakeholders.
Healthcare experience preferred.

Nice To Haves

Strong SQL and relational database skills.
Experience with data analytic tools such as Python, R, and/or SAS
Experience with Power BI, Tableau, or similar business intelligence and reporting tools.
Advanced Microsoft Excel skills, including Power Query and Power Pivot preferred.
Knowledge of data governance, data quality frameworks, metadata management, and master data management principles.
Experience supporting oncology and healthcare applications, including iKnowMed G2, Athena IDX, and AthenaOne EHR.
Working knowledge of HL7 interfaces, healthcare interoperability standards, and healthcare data exchange processes.
Experience managing duplicate record resolution, merge processes, data reconciliation, and cross-system data integrity issues.
Knowledge of data governance frameworks, stewardship practices, metadata management, and master data management solutions.
Experience supporting enterprise data warehouses, integration platforms, and reporting environments.
Familiarity with healthcare operational, clinical, financial, revenue cycle, compliance, and regulatory reporting requirements.

Responsibilities

Serve as the Texas Oncology IT lead for data quality and master data governance initiatives.
Establish and maintain data standards, definitions, business rules, metadata, data lineage, and governance documentation.
Develop and monitor data quality metrics, scorecards, dashboards, and reporting.
Identify, investigate, and resolve data quality issues, including duplicate records, data discrepancies, and integration-related concerns.
Partner with Analytics and US Oncology technical teams to support centralized and standardized enterprise data assets.
Collaborate with Operations, Compliance, HR, Legal, Revenue Cycle, and IT teams to support audits, investigate data issues, and mitigate operational and risk.
Support digital transformation, automation, interoperability, and AI initiatives by improving data quality, governance, and master data practices.
Prepare executive summaries, reports, presentations, and recommendations for leadership.
Perform other duties as assigned.