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Sr Ontology Engineer

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Fast Facts

NWEA is seeking a Senior Ontology Engineer to lead the technical development of ontologies for information systems that enhance knowledge organization and support informed decision-making. This fully remote role involves collaborating with engineering teams and ensuring ontological structures meet quality standards.

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Responsibilities: Key responsibilities include developing and maintaining ontologies, writing SPARQL queries, collaborating with teams to define information needs, and ensuring the alignment of knowledge representation with enterprise data systems.

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Skills: Advanced knowledge of ontology modeling languages (RDF, OWL, SHACL), proficiency in SPARQL and semantic data integration, and experience with semantic technologies and graph databases are essential.

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Qualifications: An advanced degree in computer science, information science, or equivalent experience is preferred, along with substantial experience with ontologies and knowledge graphs.

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Location: This position is fully remote, allowing for flexible work arrangements.

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Compensation: $105000 - $125000 / Annually



Job Title: Senior Ontology Engineer

Location: Remote 

Who We Are 

NWEA® is a division of HMH that supports students and educators through research, assessment solutions, policy and advocacy services, professional learning and school improvement services that fight for equity, drive classroom impact and push for systemic change in our educational communities. For nearly 50 years, NWEA has developed innovative pre-K–12 assessments, including their flagship interim assessment, MAP® Growth™ and their reading fluency and comprehension assessment, MAP® Reading Fluency™. For more information, visit NWEA.org to learn more. 

What you will do

The Senior Ontology Engineer acts as a technical leader working with multiple engineering teams and projects to contribute to the system design, development, integration, and maintenance. Ontology Engineers play a pivotal role in shaping our organization's knowledge structure. They are responsible for developing and managing ontologies that underpin our information systems, facilitating better data organization and knowledge discovery. Additionally, they identify opportunities to enhance our knowledge systems and lead efforts to align ontological models with business needs, supporting better data organization and informed decision-making.

Responsibilities

  • Develops and maintains logical, semantically rich, and extensible ontologies that define and structure knowledge and underpin HMH information systems and products.
  • Supports triple store development and investigation by writing SPARQL queries against RDF, OWL or validating with SHACL. Senior Ontology engineers translate user and product requirements into Abox/Tbox/Rbox requirements to execute against.
  • Supports and contributes to the definition of strategies for integration between the ontology management system and source data management repositories and ontology user interfaces.
  • Ensures the accuracy and consistency of ontological structures by performing regular quality checks and updates as needed. Senior Ontology engineers provide technical consultation and guidance on standards and best practices and ensure that the delivered product meets quality standards.
  • Collaborates with cross-functional teams to understand, define, and document their information needs and provide ontological solutions that support their objectives.
  • Creates comprehensive documentation for ontologies and knowledge graphs, making them accessible to both technical and non-technical stakeholders. Senior Ontology engineers define the necessary documentation and utilize them to communicate effectively with stakeholders.
  • Coordinates with Enterprise data governance and management teams or structures to ensure the knowledge representation is in alignment with enterprise data systems.

What you’ll need

  • Possess an advanced degree in computer science, information science, or a related quantitative field, or have equivalent professional experience.
  • Demonstrate advanced knowledge of ontology modeling languages such as RDF, OWL, or SHACL, and vocabularies like SKOS.
  • Exhibit proficiency in query languages such as SPARQL or other property graph query languages like Gremlin and openCypher.
  • Have experience with semantic data integration and the utilization of graph databases.
  • Show significant experience with ontologies, knowledge graphs, and semantic technologies, including tools like Protégé, Semaphore, PoolParty, or similar ontology management systems.
  • Be experienced with foundational/top-level ontologies, particularly Basic Formal Ontology (BFO) or Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE).
  • Possess advanced knowledge of Common Core Ontologies and methodologies, OBO Foundry methodologies, git versioning, software development practices, data normalization, ETL procedures, data integration processes and tools, entity resolution, referent tracking, and data workflow or analysis tools.
  • Be skilled in integrating multiple disparate data sets into a common vocabulary and writing effective queries for production environments.
  • Have experience with high-level programming languages and scripting/interpreted languages such as Java, JavaScript, and Python.
  • Exhibit excellent problem-solving skills and the ability to adapt quickly to new technologies, trends, and frameworks.

Salary range: 105k – 125k annually. 

Application Deadline: 

The application window for this position is anticipated to close March 2, 2025. We encourage you to apply as soon as possible. The posting may be available after this date but is not guaranteed. 

HMH is fully committed to Equal Employment Opportunity and to attracting, retaining, developing and promoting the most qualified employees without regard to race, gender, color, religion, sexual orientation, family status, marital status, pregnancy, gender identity, ethnic/national origin, ancestry, age, disability, military status, genetic predisposition, citizenship status, status as a disabled veteran, recently separated veteran, Armed Forces service medal veteran, other covered veteran, or any other characteristic protected by federal, state or local law. We are dedicated to providing a work environment free from discrimination and harassment, and where employees are treated with respect and dignity. We actively participate in E-Verify.

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Average salary estimate

$115000 / YEARLY (est.)
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$105000K
$125000K

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What You Should Know About Sr Ontology Engineer, Houghton Mifflin Harcourt

NWEA is looking for an energetic Senior Ontology Engineer to join our team and lead the development of ontologies that enhance our information systems, making knowledge organization more effective and supporting informed decision-making. Working remotely, you will collaborate with engineering teams to ensure that the ontological structures we create meet the highest quality standards and align with our business needs. Your role will involve developing and maintaining complex ontologies and writing SPARQL queries to analyze and refine data representations. We want someone who loves diving deep into information and can translate complex requirements from cross-functional teams into actionable ontology solutions. You will also ensure the accuracy of our ontological structures by performing regular quality checks and updates, while documenting your work so that it is accessible to both technical and non-technical stakeholders. If you have a knack for understanding information needs and can develop logical, semantically rich models, then the Senior Ontology Engineer position at NWEA may be just the opportunity you’ve been looking for!

Frequently Asked Questions (FAQs) for Sr Ontology Engineer Role at Houghton Mifflin Harcourt
What are the key responsibilities of a Senior Ontology Engineer at NWEA?

As a Senior Ontology Engineer at NWEA, you will be responsible for developing and maintaining logical and semantically rich ontologies that structure knowledge for our information systems. You’ll support triple store development by writing SPARQL queries, and ensure that our ontologies are accurately aligned with business requirements. Collaborating with various teams, you will document information needs, provide ontological solutions, and keep the ontological structures accurate and updated through regular quality checks.

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What qualifications do I need to become a Senior Ontology Engineer at NWEA?

To qualify for the Senior Ontology Engineer position at NWEA, you should possess an advanced degree in computer science, information science, or a related field. Alongside your degree, substantial experience with ontologies, knowledge graphs, and semantic technologies is required. Familiarity with ontology modeling languages such as RDF, OWL, and SPARQL is essential, as is the ability to write effective queries for production environments. Experience with programming languages like Java, JavaScript, or Python will also be beneficial.

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What skills are essential for a Senior Ontology Engineer at NWEA?

A Senior Ontology Engineer at NWEA should have advanced knowledge of ontology modeling languages including RDF and OWL. Proficiency in SPARQL for writing queries and integrating semantic data is crucial. Experience with graph databases, semantic technologies, and tools for ontology management is also important. You should demonstrate excellent problem-solving skills and adaptability to new technologies, alongside the ability to integrate multiple data sets into a common vocabulary.

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Is the Senior Ontology Engineer position at NWEA remote?

Yes! The Senior Ontology Engineer position at NWEA is fully remote, allowing you to work from anywhere. This flexible work arrangement provides an excellent opportunity to balance your professional responsibilities with personal commitments while being part of a dynamic organization focused on improving educational outcomes.

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What is the expected salary range for a Senior Ontology Engineer at NWEA?

The expected salary for a Senior Ontology Engineer at NWEA ranges from $105,000 to $125,000 annually. This competitive compensation reflects the importance of the role in contributing to our team's success and the knowledge systems that underpin our information products.

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Common Interview Questions for Sr Ontology Engineer
Can you explain your experience with ontology modeling languages and tools?

When answering this question, highlight your familiarity with key ontology modeling languages such as RDF and OWL. Discuss specific projects where you used these languages to design ontologies. Be sure to mention any tools you've used, such as Protégé or similar ontology management systems, and how they aided in structuring and representing knowledge effectively.

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How do you approach developing an ontology for a new information system?

Describe your process which might include gathering requirements from stakeholders to understand their information needs, defining the scope of the ontology, and iteratively developing the model. Be sure to discuss the importance of collaboration with other engineering teams and performing quality checks to refine and validate the ontology.

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What are some challenges you've faced in managing ontologies and how did you overcome them?

When answering this question, share a specific challenge, such as ensuring data consistency or integrating diverse data sources. Explain the steps you took to address it, such as implementing regular maintenance checks or refining the ontology based on user feedback, and the positive outcomes of your actions.

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Explain a SPARQL query you wrote and what it accomplished.

Be prepared to discuss a specific SPARQL query, including its purpose and the data it targeted. Describe the structure of the query and how it contributed to your project, such as retrieving data for analysis or validating ontological structures.

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How do you ensure an ontology remains relevant and up-to-date?

Discuss your approach to performing regular quality checks, collaborating with team members to gather feedback, and keeping abreast of changes in business needs. Emphasize the importance of documentation to track revisions and ensure all stakeholders are informed about updates.

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What strategies do you use for integrating multiple data sources into a common ontology?

Outline your approach, which may involve conducting a thorough analysis of the data sources, defining a common vocabulary, and using transformation tools to align the datasets to the ontology structure. Explain the significance of collaboration with data owners to maintain alignment with the business.

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What role does documentation play in your ontology development process?

Emphasize the importance of documentation in your work as it serves as a reference for technical and non-technical stakeholders. Discuss how you document the development process, the structure of the ontology, and the reasoning for decisions made. Good documentation facilitates collaboration and supports future enhancements.

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Can you provide an example of a successful project you led as an ontology engineer?

Share details about a specific project, focusing on your leadership role. Discuss the challenges faced, the strategies implemented, and the results achieved. Highlight how your work contributed to improving knowledge organization or decision-making in the information system.

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How do you stay current with advancements in semantic technologies?

Discuss the resources you utilize to stay updated, such as attending webinars, following leading blogs, participating in online communities, or engaging with continuing education opportunities. Express your commitment to ongoing learning and adapting to new technologies in the field.

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What do you consider to be best practices when working with knowledge graphs?

In your response, talk about best practices such as maintaining clear definitions between concepts, ensuring accuracy in data representation, promoting collaboration across departments, and continuously updating the graph as new information becomes available. Discuss how these practices enhance the overall effectiveness of knowledge systems.

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DATE POSTED
April 4, 2025

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