Role Description A Data Management Manager is responsible for leading enterprise data strategy, governance, and transformation initiatives in a fast-paced, client-driven environment, ensuring data integrity, accessibility, and compliance while supporting large-scale system implementations and business process improvements. - Required Travel: 20% - All interviews will be held on Microsoft Teams Video Key Responsibilities - Data Strategy & Transformation: Lead data initiatives tied to system implementations, migrations, and process improvements to align with business objectives. - Data Governance & Compliance: Establish and enforce data standards, policies, and controls to ensure accuracy, security, and regulatory compliance. - System & Integration Oversight: Partner on ERP and data platform implementations (e.g., NetSuite, SAP, Oracle), ensuring seamless data flow and structure. - Data Quality & Migration: Oversee data cleansing, validation, and migration efforts during system transitions or upgrades. - Stakeholder Collaboration: Work cross-functionally with finance, operations, and IT teams to translate business needs into scalable data solutions. - Client/Project Leadership: Manage multiple projects simultaneously, providing guidance, timelines, and deliverables in a consulting-style environment. Qualifications - Education: Bachelor’s degree in Information Systems, Data Management, Finance, or related field. - Experience: 5+ years in data management, ERP implementations, or business transformation environments. - Technical Skills: Strong experience with SQL, ERP systems (NetSuite, SAP, Oracle), data warehousing, and reporting tools (Power BI, Tableau). - Project Management: Proven ability to lead complex, cross-functional projects with multiple stakeholders. - Communication: Strong ability to translate technical concepts into business insights and recommendations. Requirements - Common Performance Metrics: - Accuracy and success rate of data migrations and system implementations - Data quality, consistency, and governance adherence - Project delivery timelines and stakeholder satisfaction - Improvement in reporting efficiency and business decision-making speed Benefits - 401(k) matching - Competitive salary - Dental insurance - Health insurance - Opportunity for advancement - Paid time off - Training & development - Vision insurance Company Description This is a remote position.

Senior Oncology Data Specialist Location: Remote USA Department: Clinical Quality Registry Services Schedule: Part-time, 20 hours Salary: $28.35 - $39.52 per hour #LI-Remote Life at Ascension: Where purpose meets opportunity Ascension is a leading nonprofit Catholic health system with a culture and associate experience grounded in service, growth, care and connection. We empower our 99,000+ associates to bring their skills and expertise every day to reimagining healthcare, together. Recognized as one of the Best 150+ Places to Work in Healthcare and a Military-Friendly Gold Employer, you’ll find an inclusive and supportive environment where your contributions truly matter. Benefits that help you thrive - Comprehensive health coverage: medical, dental, vision, prescription coverage and HSA/FSA options - Financial security & retirement: employer-matched 403(b), planning and hardship resources, disability and life insurance - Time to recharge: paid time off (PTO) and holidays - Career growth: Ascension-paid tuition (Vocare), reimbursement, ongoing professional development and online learning - Emotional well-being: Employee Assistance Program, counseling and peer support, spiritual care and stress management resources - Family support:parental leave, adoption assistance and family benefits - Other benefits: optional legal and pet insurance, transportation savings and more Benefit options and eligibility vary by position, scheduled hours and location. Benefits are subject to change at any time. Your recruiter will provide the most up-to-date details during the hiring process. How you’ll make an impact in this role Perform complex analysis utilizing specialty databases to extract patient data from electronic medical records for analysis of cancer incidence data. - Retrieve and upload manual case finding lists into cancer registry software as required by market assignments. - Screen disease indices, pathology reports, radiology reports, and other clinical documents to identify reportable cancer cases for case finding. - Perform primary data abstraction duties for oncology measures and registries while ensuring high levels of abstraction accuracy and alignment with organizational quality standards in compliance with all oncology regulatory standards. - Maintain the long-term follow up process of data collection and input for all cancer registry patients. - Collect data for National Cancer Database special studies as required. What minimum requirements you’ll need Licensure / Certification / Registration: - Oncology Data Specialist credentialed from the National Cancer Registrars Association (NCRA) obtained prior to hire date or job transfer date required. - Registrar specializing in Tumors preferred. Education: - High School diploma equivalency with 2 years of cumulative experience. Successful completion of a NCRA-Accredited Certificate Program required OR Associate's degree/Bachelor's degree OR 4 years of applicable cumulative job specific experience required. Equal employment opportunity employer Ascension provides Equal Employment Opportunities (EEO) to all associates and applicants for employment without regard to race, color, religion, sex/gender, sexual orientation, gender identity or expression, pregnancy, childbirth, and related medical conditions, lactation, breastfeeding, national origin, citizenship, age, disability, genetic information, veteran status, marital status, all as defined by applicable law, and any other legally protected status or characteristic in accordance with applicable federal, state and local laws. Fraud prevention notice Prospective applicants should be vigilant against fraudulent job offers and interview requests. Scammers may use sophisticated tactics to impersonate Ascension employees. To ensure your safety, please remember: Ascension will never ask for payment or to provide banking or financial information as part of the job application or hiring process. Our legitimate email communications will always come from an @ascension.org email address; do not trust other domains, and an official offer will only be extended to candidates who have completed a job application through our authorized applicant tracking system. E-Verify statement Employer participates in the Electronic Employment Verification Program.

• Build and maintain high-volume, scalable data pipelines using Apache Kafka and Apache Spark, supporting both real-time and batch data processing needs. • Design, develop, and optimize data ingestion, transformation, and integration workflows across enterprise systems. • Ensure data quality, consistency, and integrity across four (4) disparate data sources, implementing validation, cleansing, and reconciliation processes. • Develop and maintain SQL-based data solutions, including complex queries, stored procedures, performance tuning, and data modeling. • Collaborate with data analysts, product owners, and application teams to define data requirements and ensure alignment with business needs. • Implement monitoring, logging, and alerting mechanisms to ensure reliability and observability of data pipelines. • Support data architecture design and contribute to best practices for scalable and secure data engineering solutions. • Ensure compliance with federal data governance, security, and privacy requirements. • Participate in Agile ceremonies and support iterative development and delivery of data capabilities. • Troubleshoot and resolve data pipeline issues, ensuring minimal disruption to downstream systems and reporting.

• Design, build, and maintain scalable data pipelines and APIs on Google Cloud Platform. • Develop automated workflows and data platforms that support analytics, reporting, and AI/ML use cases. • Implement best practices for data security, governance, CI/CD, and automated deployment. • Collaborate with data engineers, architects, data scientists, and business stakeholders. • Produce high-quality, reusable code and mentor team members on best practices. • Support testing, deployment, monitoring, and production troubleshooting.