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Knowledge Manager Jobs in Berkeley, CA (NOW HIRING)

Gotion, Inc.

Program Manager

Fremont, CA · On-site

Organize key program information to ensure Program continuity and to contribute to knowledge management. Required Qualifications: (3-5 key points required) * * The ideal candidate will have/be:

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All JobsKnowledge JobsKnowledge Manager JobsKnowledge Manager Jobs in Berkeley, CA

Knowledge Manager information

See Berkeley, CA salary details

$53.3K

$105.4K

$150.6K

How much do knowledge manager jobs pay per year?

As of Aug 16, 2026, the average yearly pay for knowledge manager in Berkeley, CA is $105,447.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,800.00 and $126,700.00 per year, depending on experience, location, and employer.

What is a knowledge manager?

A knowledge manager ensures that company policies, strategies, and initiatives are properly documented and accessed by authorized users. These professionals support process improvement and decision-making and may work in a variety of industries. As a knowledge manager, your duties involve organizing a knowledge database, analyzing the effectiveness of knowledge management programs, and acting as mediator to answer client and staff questions about related products and practices. To pursue a career as a knowledge manager, you typically need a degree in business, information technology, or a related field and relevant work experience. Additional qualifications include interpersonal, organizational, and project management skills, as well as attention to detail and resourcefulness.

What does a knowledge manager do?

A Knowledge Manager is responsible for organizing, managing, and optimizing the knowledge assets within an organization. They develop strategies and systems for capturing, storing, sharing, and utilizing information to improve efficiency, collaboration, and decision-making. Knowledge Managers often work with digital platforms, facilitate training, and encourage a culture of knowledge sharing among employees. Their role is crucial in ensuring that valuable organizational knowledge is preserved and accessible to those who need it.

What are the key skills and qualifications needed to thrive as a knowledge manager, and why are they important?

To thrive as a Knowledge Manager, you need expertise in information management, content curation, and organizational strategy, often supported by a degree in library science, information systems, or a related field. Familiarity with knowledge management systems (KMS), collaboration platforms like SharePoint or Confluence, and relevant certifications such as Certified Knowledge Manager (CKM) are typically required. Strong communication, analytical thinking, and stakeholder engagement skills help drive knowledge-sharing initiatives and foster a culture of continuous learning. These skills ensure that organizational knowledge is efficiently captured, shared, and utilized, leading to improved decision-making and innovation.

How does a knowledge manager typically collaborate with other departments to ensure effective knowledge sharing?

Knowledge Managers work closely with various departments such as IT, HR, and operations to identify knowledge gaps, develop systems for information sharing, and promote best practices. They often facilitate workshops, create knowledge bases, and establish guidelines to ensure that valuable organizational knowledge is accessible and up-to-date. Regular interaction with team leaders and subject matter experts is essential to capture insights and tailor knowledge management strategies that support business objectives.

What is the difference between Knowledge Manager vs Content Specialist?

AspectKnowledge ManagerContent Specialist
Required CredentialsBachelor's degree, certifications in knowledge management or information systemsBachelor's degree, certifications in content creation or digital marketing
Work EnvironmentCorporate, IT, or organizational settings focusing on information systemsMarketing, media, or digital teams creating and managing content
Employer & Industry UsageUsed across industries to manage organizational knowledge assetsCommon in marketing, media, and digital content industries
Search & Comparison IntentUnderstanding roles related to organizational knowledgeComparing content creation and management roles

The Knowledge Manager focuses on organizing, maintaining, and improving organizational knowledge assets, often working with information systems and internal data. In contrast, the Content Specialist primarily creates, edits, and manages digital content for marketing or communication purposes. While both roles require strong communication skills and relevant certifications, their work environments and objectives differ significantly.

How much do knowledge managers make in the US?

Knowledge managers in the US typically earn between $70,000 and $120,000 annually, depending on experience, industry, and location. Senior roles or those with specialized skills in information systems or enterprise content management may earn higher salaries. Compensation often includes benefits such as health insurance and professional development opportunities.
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Knowledge Manager jobs near you
Infographic showing various Knowledge Manager job openings in Berkeley, CA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution, with an average salary of $105,447 per year, or $50.7 per hour.

Senior Ontologist - Knowledge Graph & Identity

Samba

San Francisco, CA • On-site, Remote

$180K - $230K/yr

Full-time

Re-posted 11 days ago

Job description

Samba is a media intelligence company. We know what the world is watching, reading, and thinking about — in real time, at scale, across every screen. Our data exists with the consent of over a billion people, organized into the most complete picture of consumer attention ever built. The biggest brands in the world use that picture to make smarter decisions. We think it’s the most interesting data asset on the planet, because it’s the most culturally relevant. 

As Senior Ontologist on Samba TV's Knowledge Graph & Identity team, you will own the design, development, and governance of the semantic data models and ontological frameworks that sit at the foundation of Samba's knowledge graph. You are the domain authority for how Samba represents and relates the entities that matter most to our business - and you ensure that representation is rigorous, scalable, and aligned with industry standards.

This is a hands-on technical role. You will spend the majority of your time designing ontologies, writing SPARQL, building knowledge graph pipelines, and working closely with data engineering and data science peers to put your models into production. You bring enough breadth in ML and AI to leverage embedding-based and LLM-augmented approaches where they strengthen the graph, and you contribute meaningfully to entity resolution and identity linking work that depends on the semantic layer you define.

This role reports to the Data Science Manager, Knowledge Graph & Identity.

What You'll Do:

Ontology Design & Governance

  • Own the end-to-end design, development, and versioning of Samba TV's core ontologies in RDF/RDFS/OWL - defining entity classes, properties, hierarchies, and constraints that accurately model Samba's data domain at scale

  • Author and maintain SHACL shapes for post-load graph validation, consistency checking, and data quality enforcement

  • Define and document derived-attribute schemas - genre affinity, brand affinity, topic affinity, lifecycle signals, and viewing summaries - and own the logical definitions that govern how raw events become durable graph attributes

  • Establish ontology design standards, change management processes, and versioning practices; evaluate alignment with W3C standards and relevant industry schemas (Schema.org, EIDR, DDEX, W3C PROV)

  • Lead ontology design reviews with product, data engineering, and data science stakeholders - articulating trade-offs between expressivity, scalability, and query performance clearly

Event-to-Ontology Derivation

  • Define the aggregation and scoring logic that transforms raw TV viewership and web activity events into the durable affinities, summaries, and inferred signals that live in the graph

  • Co-own derivation pipeline design with data engineering - specifying transformation logic, intermediate schemas, and validation checkpoints for Databricks/Spark pipelines that feed the materialized graph substrate

  • Reason carefully about what belongs in the graph vs. what should remain virtualized in the data lake - balancing query performance against storage and refresh cost

Knowledge Graph Development & AI Integration

  • Build and maintain production-quality knowledge graph pipelines in Python and SPARQL - well-tested, documented, and scalable to Samba's data volumes

  • Design and implement entity resolution and record linkage pipelines that map real-world entities (content titles, devices, audiences, advertisers) to canonical knowledge graph nodes

  • Develop enrichment workflows that integrate third-party data sources (metadata providers, identity vendors, web sources) into Samba's knowledge graph in a consistent, governed way

  • Apply embedding-based and LLM-augmented approaches to ontology mapping, entity disambiguation, and semantic similarity problems

  • Support content and semantic embedding pipelines that feed into the vector store and underpin GraphRAG-based AI solutions

Cross-functional Collaboration & Mentorship

  • Partner with data engineering and platform teams to ensure the knowledge graph is integrated, queryable, and production-ready at scale

  • Collaborate with product to translate business requirements into ontological and graph data model decisions

  • Formally mentor Ontology Engineers and junior data scientists on semantic modeling, SHACL design patterns, and graph best practices

  • Lead internal technical talks and workshops on ontology, knowledge graph, and semantic web topics

Who You Are:

Must-Haves

  • 5–8 years of hands-on experience in ontology engineering, semantic data modeling, or knowledge graph development - with a demonstrable track record of production ontologies at scale

  • Deep expertise in W3C semantic web standards: RDF, RDFS, OWL, SPARQL 1.1, and SHACL - with hands-on experience building and validating graph schemas in a production triplestore (Amazon Neptune, Stardog, GraphDB, Jena, or equivalent)

  • Strong Python - production-quality, well-tested code; comfortable building data pipelines and graph processing workflows

  • First-principles understanding of description logics, ontology design patterns, and the practical trade-offs between OWL expressivity and triplestore scalability

  • Hands-on experience with entity resolution, record linkage, or deduplication at scale - mapping messy, multi-source real-world data to clean ontological representations

  • Bachelor's degree required in Computer Science, Information Science, Computational Linguistics, Mathematics, or a related field; Master's or PhD strongly preferred

  • Strong communicator - able to defend ontological modeling decisions in design reviews and explain trade-offs to non-specialist stakeholders

Strongly Preferred

  • Hands-on experience with Amazon Neptune or Stardog - including data virtualization (Neptune Orion or Stardog Virtual Graphs) over data lake sources

  • Experience designing aggregation and derivation logic that converts raw behavioral event data into durable, graph-resident derived attributes

  • Domain knowledge in media, entertainment, or ad tech - TV viewership (ACR/STB), digital audience modeling (device graphs, identity resolution), or ad exposure data

  • Familiarity with industry content and identity schemas: EIDR, Schema.org VideoObject, DDEX, or equivalent

  • Experience with embedding models, vector databases (Milvus, Pinecone, Weaviate), and GraphRAG architectures (LangChain/LlamaIndex)

  • Familiarity with GNN-based approaches to knowledge graph reasoning or entity resolution a plus

  • Working knowledge of PySpark and Databricks for large-scale transformation pipelines

Samba is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.  We strive to empower connection with one another, reflect the communities we serve, and tackle meaningful projects that make a real impact.
 
Samba may collect personal information directly from you, as a job applicant, Samba may also receive personal information from third parties, for example, in connection with a background, employment or reference check, in accordance with the applicable law. For further details, please see Samba's Applicant Privacy Policy. For residents of the EU , Samba Inc. is the data controller.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.