This role is responsible for the collection, retrieval, and analysis of data on patients with cancer and certain benign tumors. Responsible for follow-up information and data entry maintaining current knowledge of and disseminating updates from the Commission on Cancer standards. The cancer registry department serves as primary contact providing guidance of activities aimed at achieving and maintaining cancer program accreditations. This includes interpretation and education of new standards, assessment of compliance, identification of opportunities for improvement, and facilitation efforts to achieve and maintain compliance. Initiates and/or coordinates clinical data collection and submits reports using statistical techniques. Maintains a sense of pride and ownership for the program. Maintains confidentiality of all interactions. Schedule: - Full-time | 64 hours every two weeks | Remote - Days | 8-hour shifts | 7:30am – 4pm - Occasional requirements to be onsite Pay and Benefits: - Starting pay begins at $25.20 per hour; exact wage determined by years of related experience - Pay range: $25.20 - $37.81 per hour - Tuition reimbursement and college grant programs available - Full-time benefits: Medical, dental, PTO, retirement, employee discounts and more! Qualifications: - Associate degree from an accredited school of Health Information Technology or Cancer Registry Management or bachelor's degree from an accredited school of Health Information Technology required. - 1 year of experience in Cancer Registry required - 2 years of experience in health care required - Certification options: - Oncology Data Specialist (ODS-C) Certification required, can be obtained within 2 years of hire or - Oncology Data Specialist (ODS-C) Certification and Registered Health Information Technician (RHIT) or - Oncology Data Specialist (ODS-C) Certification and Registered Health Information Administrator (RHIA) or - 3 years Current Certified Tumor Registrar (CTR), 3-years’ experience in a hospital-based registry preferred - EPIC and CRStar experience preferred CentraCare has made a commitment to diversity in its workforce. All individuals including, but not limited to, individuals with disabilities, are encouraged to apply. CentraCare is an EEO/AA employer.

• Collaborate & Strategize: Partner closely with business stakeholders to understand their challenges and design end-to-end architecture that solves complex business problems. • Build & Maintain Data Models: Design, develop, and own robust, efficient, and scalable data models in Snowflake and Iceberg using dbt and advanced SQL. • Orchestrate & Automate: Build and manage reliable data pipelines and CI/CD workflows using tools like Airflow, Python, and Terraform to ensure data is fresh, trustworthy, and infrastructure is version-controlled. • Champion Data Quality: Implement rigorous testing, documentation, and data governance practices to maintain a single source of truth. • Enable Analytics & Workflows: Act as the Product Owner and Tech Lead for your data domains, taking responsibility for the end-to-end data product delivery– from raw ingestion to data models enabling analytics and data apps in tools like Tableau and Retool. • Innovate with AI: Help us build our next-generation data infrastructure by integrating AI capabilities (like Snowflake Cortex AI) to democratize analytics and empower the business. • Architect Observability: Implement monitoring and alerting frameworks (e.g., dbt packages or Monte Carlo monitors) to proactively catch "silent" data failures before stakeholders do.

• Design, implement, and optimize Elasticsearch clusters for high-performance querying and data retrieval. • Build and manage Elasticsearch indexes, ensuring data is stored, indexed, and queried efficiently. • Build and optimize data storage solutions like data lakes and warehouses. • Integrate structured and unstructured data from various internal and external systems to create a unified view for analysis. • Ensure data accuracy, consistency, and completeness through rigorous validation, cleansing, and transformation processes. • Maintain comprehensive documentation for data processes, tools, and systems while promoting best practices for efficient workflows. • Collaborate with product managers, and other stakeholders to gather requirements and translate them into technical solutions. • Participate in requirement analysis sessions to understand business needs and user requirements. • Provide technical insights and recommendations during the requirements-gathering process. • Participate in Agile development processes, including sprint planning, daily stand-ups, and sprint reviews. • Work closely with Agile teams to deliver software solutions on time and within scope. • Adapt to changing priorities and requirements in a fast-paced Agile environment. • Conduct thorough testing and debugging to ensure the reliability, security, and performance of applications. • Write unit tests and validate the functionality of developed features and individual elements. • Writing integration tests to ensure different elements within a given application function as intended and meet desired requirements. • Identify and resolve software defects, code smells, and performance bottlenecks. • Stay updated with the latest technologies and trends in full-stack development. • Propose innovative solutions to improve the performance, security, scalability, and maintainability of applications. • Continuously seek opportunities to optimize and refactor existing codebase for better efficiency. • Stay up-to-date with cloud platforms such as AWS, Azure, or Google Cloud Platform. • Collaborate effectively with cross-functional teams, including testers, and product managers.

• Design and implement data pipelines for the collection, storage, and transformation of data from a variety of sources • Develop and maintain data models and schema to support data analysis and reporting • Write and maintain ETL jobs to extract, transform, and load data into our data warehouse • Collaborate with ML engineers, data analysts, and other stakeholders to understand data requirements and develop solutions to support data-driven decision-making • Monitor and optimize data pipelines and processes to ensure data quality and performance