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Remote Ontology Engineer Jobs in Tennessee (NOW HIRING)

Senior Director, Data Architecture

Franklin, TN · Remote

$64.75 - $86.75/hr

Remote-USA We are hiring a Senior Director of Enterprise Data Architecture & Standards to bring ... Define a common language, grounded in healthcare context - Develop a shared ontology and enterprise ...

Remote Ontology Engineer information

What is a remote ontology engineer?

A Remote Ontology Engineer is a professional who designs, develops, and maintains ontologies—structured frameworks for organizing information—while working from a remote location. They use their expertise in knowledge representation, semantic web technologies, and data modeling to ensure that information systems can interpret and connect data effectively. Their work is crucial in fields like artificial intelligence, data integration, and information retrieval, as they help systems 'understand' relationships between different pieces of data. Remote Ontology Engineers often collaborate with developers, data scientists, and domain experts using online tools and communication platforms.

How does a remote ontology engineer typically collaborate with cross-functional teams while working off-site?

As a Remote Ontology Engineer, you will frequently collaborate with data scientists, software developers, and subject matter experts through virtual meetings, shared documentation, and project management tools. Effective communication and proactive documentation are key, as you'll often need to clarify domain concepts and ensure semantic consistency across distributed teams. Many organizations use agile methodologies, so you can expect regular stand-ups and sprint planning sessions to stay aligned on project goals and deliverables. Building strong relationships remotely requires initiative, responsiveness, and a willingness to leverage digital collaboration platforms.

What are the key skills and qualifications needed to thrive as a remote ontology engineer, and why are they important?

To thrive as a Remote Ontology Engineer, you need a strong background in computer science, knowledge representation, and formal logic, typically supported by a relevant degree and experience in semantic technologies. Familiarity with ontology development tools (such as Protégé), semantic web standards (like OWL and RDF), and querying languages (SPARQL) is essential. Excellent problem-solving, communication, and self-motivation skills help you collaborate effectively in distributed teams and translate complex domain knowledge into structured ontologies. These skills are crucial for building robust, interoperable knowledge models that support data integration and intelligent applications across industries.

What is the difference between Remote Ontology Engineer vs Data Scientist?

AspectRemote Ontology EngineerData Scientist
Required CredentialsMaster's in Computer Science, Knowledge Engineering, or related fields; certifications in ontology modelingDegree in Data Science, Statistics, or related; certifications in data analysis or machine learning
Work EnvironmentCollaborates with AI, semantic web, and knowledge management teams; often in tech or research industriesWorks with data analysis, modeling, and visualization teams; across various industries including tech, finance, and healthcare
Employer & Industry UsageUsed in AI, semantic web, and knowledge-based systemsApplied in analytics, predictive modeling, and business intelligence

While both roles require technical expertise and involve working with complex data, Remote Ontology Engineers focus on developing and managing ontologies for knowledge representation, whereas Data Scientists analyze data to extract insights. The roles often overlap in tech environments but serve different core functions.

What are popular job titles related to Remote Ontology Engineer jobs in Tennessee?

For Remote Ontology Engineer jobs in Tennessee, the most frequently searched job titles are:

What cities in Tennessee are hiring for Remote Ontology Engineer jobs?

Cities in Tennessee with the most Remote Ontology Engineer job openings:

Senior Director, Data Architecture

Revecore

Franklin, TN • Remote

$64.75 - $86.75/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago


Revecore rating

8.1

Company rating: 8.1 out of 10

Based on 22 frontline employees who took The Breakroom Quiz


Job description

Start your next chapter at Revecore! For over 25 years, we've been at the forefront of specialized claims management, helping healthcare providers recover meaningful revenue to enhance quality patient care in their communities. We're powered by people, driven by technology, and dedicated to our clients and employees.
As part of our team, you'll be rewarded with:

  • Comprehensive medical, dental, vision, and life insurance benefits from the start of your employment
  • 12 paid holidays and flexible paid time off
  • 401(k) contributions
  • Employee Resource Groups that build community
  • Career growth opportunities
  • An excellent work/life balance


Location:Remote-USA

We are hiring a Senior Director of Enterprise Data Architecture & Standards to bring order and shared meaning to data that today lives across Customer Success, Finance, Data Science, Engineering, and Operations. With most of our enterprise data now consolidated in Snowflake, the opportunity - and the challenge - is no longer access to data, but agreement on what it means. This role owns that problem end to end: establishing enterprise data standards, a data catalog, and a business ontology so that every team, from an embedded analyst in Finance to a data scientist modeling patient financial outcomes, is working from the same definitions, the same lineage, and the same source of truth.

This is a hands-on architecture role, not a management position. You will spend most of your time in Snowflake, in data models, in cataloging tools, and in working sessions with stakeholders - not building a team beneath you. You will report to the SVP of AI, Data & Data Science and operate as the senior-most technical authority on data standards, taxonomy, and governance across the enterprise.

What You'll Do

  • Establish enterprise data standards - Design and drive adoption of an enterprise data standards program covering naming conventions, business/technical metadata, data quality rules, and reporting definitions across the Snowflake data warehouse.
  • Build and own the data catalog - Select, implement, or extend a data catalog that makes data discoverable and trustworthy, with clear ownership, definitions, sensitivity classifications, and usage guidance for every core data asset.
  • Define a common language, grounded in healthcare context - Develop a shared ontology and enterprise data dictionary that reconciles how Customer Success, Finance, Data Science, Engineering, and Operations each define core entities and metrics (e.g., "claim," "account," "client," "revenue recognized"), applying working knowledge of healthcare revenue cycle, claims, patient financial, and provider/payer data to ensure definitions reflect the realities of the business.
  • Establish lineage and reporting standards - Define and implement data lineage standards so any consumer can trace a metric or field from source to consumption, while partnering with embedded analytics teams in Data Science, Operations, and Finance to align reporting definitions and move toward a single set of certified reports and semantic models.
  • Architect hands-on - Serve as the enterprise data architect for how data is modeled, organized, and governed within Snowflake, working directly alongside data engineering on schema design, domain modeling, and platform architecture decisions.
  • Drive cross-functional alignment and sustainable governance - Act as the connective tissue between technical teams and business stakeholders, translating between business concepts and data models, and establishing decision rights, change-management processes, and governance forums (e.g., a data council) so standards remain living, adopted practices.
  • What You Bring
  • 10+ years in data architecture, data management, or enterprise data roles, including direct, hands-on experience building or scaling data catalogs, data dictionaries, taxonomies, or ontologies across a complex organization.
  • Deep hands-on platform and tooling experience - Snowflake (or a comparable cloud data warehouse) including data modeling, schema design, and architecture tradeoffs, plus direct experience with data cataloging/metadata management tools (e.g., Snowflake Horizon, Collibra, Alation, Atlan, DataHub, Purview) and, integration of legacy data sources (e.g. RDBMS) lineage tooling and practices.
  • Proven ability to build enterprise-wide agreement through influence - a track record of aligning functions with genuinely different vocabularies and incentives (Finance, Data Science, Operations, Customer Success, Engineering), backed by strong written and verbal communication skills and the ability to facilitate consensus among stakeholders who don't naturally agree.
  • Healthcare domain experience - ideally within the healthcare revenue cycle, payer/provider, or patient financial services lifecycle, with comfort in clinical, claims, or billing data concepts.
  • Strong technical foundations as a senior IC architect - solid data modeling fundamentals (dimensional modeling, entity-relationship modeling, semantic layers), familiarity with modern data stack components (ELT/ETL, orchestration, BI/semantic tools like dbt, Looker, Power BI, or Tableau), and a track record operating hands-on at a senior individual-contributor level while also representing data architecture in leadership forums.

Nice to Have

  • Experience with data governance frameworks (e.g., DAMA-DMBOK) and formal data stewardship programs.
  • Familiarity with healthcare data standards (e.g., X12, HL7/FHIR, CPT/ICD coding) and regulatory considerations (HIPAA) as they relate to data classification and access.
  • Experience introducing or scaling ontology/knowledge-graph approaches to support AI and data science initiatives.

What Success Looks Like

  • Common definitions, one source of truth - A published, adopted enterprise data dictionary and ontology, with core business entities and metrics defined once and referenced consistently across Finance, Customer Success, Data Science, Operations, and Engineering.
  • A functioning data catalog - A live data catalog covering the highest-value Snowflake datasets, with owners, definitions, and lineage documented and kept current.
  • Traceable lineage - Documented lineage for key reporting metrics from source system to consumption, reducing time spent reconciling conflicting numbers across teams.
  • Aligned reporting - A reduced number of duplicate or conflicting reports and metric definitions, with embedded analytics teams operating from shared, certified data models.
  • Durable governance - A governance structure (council, stewardship roles, or equivalent) that stakeholders across the business recognize and actively participate in.

Work at Home Requirements:

  • A quiet, distraction-free environment to work from in your home.
  • A secure home internet connection with speeds >20 Mbps for downloads and >10 Mbps for uploads is required.
  • The workspace area accommodates all workstation equipment and related materials and provides adequate surface area to be productive.


Employment is contingent upon eligibility to work in the U.S., employment history verification, and a background check.
Revecore is an equal opportunity employer that does not discriminate based on race, color, religion, sex or gender, gender identity or expression, sexual orientation, national origin, age, disability status, veteran status, genetic information, or any other legally protected status. We believe that a diverse workforce fosters innovation and creativity, enriches our culture, and enables us to better serve the needs of our clients and communities. We welcome and encourage individuals of all backgrounds, perspectives, and abilities to apply.
Must reside in the United Stateswithin one of the states listed below:
Alabama, Arkansas, Florida, Georgia, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Massachusetts Michigan, Minnesota, Mississippi Missouri, Nebraska, New Hampshire North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Vermont, Virginia, West Virginia and Wisconsin


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