Data Discovery Engineer

RadNet•UNAVAILABLE, OH

About The Position

Artificial Intelligence; Advanced Technology; The very best in patient care. With decades of expertise, RadNet is Leading Radiology Forward. With dynamic cross-training and advancement opportunities in a team-focused environment, the core of RadNet’s success is its people with the commitment to a better healthcare experience. When you join RadNet as a Data Discovery Engineer, you will be joining a dedicated team of professionals who deliver quality, value, and access in the 21st century and align all stakeholders- patients, providers, payors, and regulators to achieve the best clinical outcomes.

Requirements

Experience working with data governance frameworks and metadata management.
Strong ability to engage with both business and technical stakeholders, ensuring alignment.
Excellent analytical skills, with the ability to understand and document complex business processes.
Ability to drive data stewardship initiatives, ensuring accountability and proper classification.
Strong written and verbal communication skills, with experience in documentation and training.
Familiarity with modern data discovery techniques, including AI-driven search.
Experience with enterprise data catalog tools and metadata management platforms.
Familiarity with data governance best practices and regulatory compliance standards.
Previous experience in business intelligence, analytics, or data management roles.
Exposure to AI-driven query generation and intelligent search solutions.

Nice To Haves

Exercise sound judgement and an ability to remain professional in all situations.
Demonstrate effective and professional communication, interpersonal skills and respect with patients, guests & colleagues.
Have a structured work-approach, understand complex problems and be able to prioritize work in a fast-paced environment.

Responsibilities

Partner with data stewards, governance teams, and business leaders to ensure data is well-defined and properly cataloged.
Work closely with business users to understand how data is used and ensure documentation reflects real-world applications.
Act as a liaison between technical and business teams, translating data needs into cataloging and governance priorities.
Support data literacy initiatives, ensuring that teams can confidently access and use data.
Build and maintain a trusted data catalog, providing clear definitions, business context, and lineage tracking.
Define and enforce metadata standards to ensure consistency across the organization.
Ensure that cataloged data is accurate, up-to-date, and aligned with business processes.
Improve data accessibility by refining documentation, making it easy for users to search and understand.
Align data cataloging efforts with the organization’s data governance and compliance frameworks.
Work with governance teams to establish policies that ensure data integrity and responsible usage.
Support data quality initiatives by ensuring metadata includes ownership, accuracy, and classification details.
Promote strong data stewardship practices, ensuring accountability for data management.
Ensure business terms, metadata, and catalog definitions are structured to enhance AI-driven data retrieval.
Collaborate with technical teams to improve data discoverability through advanced search and intelligent recommendations.
Work with governance and security teams to ensure AI-enabled data access aligns with compliance and security policies.
Develop a deep understanding of business processes and key datasets, ensuring that data is properly contextualized.
Work with business users to translate data needs into cataloging requirements, making data easier to find and use.
Provide training and support to help teams effectively navigate and leverage the data catalog.
Act as a trusted resource, ensuring that the relationships between data elements are well-documented and easily understood.