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RH
Robert Half
Data and Knowledge Engineer
Job Description
Data & Knowledge EngineerCompany OverviewA leading artificial intelligence and advanced analytics organization is seeking a Data & Knowledge Engineer to help power next-generation AI and decision-support platforms. Based in Los Angeles, California, the company specializes in integrating complex data from disparate sources into unified intelligence systems that support advanced analytics, automation, and operational decision-making. This is an opportunity to work on mission-critical initiatives involving large-scale data, knowledge graphs, and AI-driven applications.
Role SummaryThe Data & Knowledge Engineer will lead the onboarding, transformation, and governance of complex multimodal data into scalable data and knowledge platforms. This role focuses on integrating structured and unstructured data sources, designing reusable data pipelines, developing entity resolution frameworks, and enabling high-quality data for analytics, retrieval, AI workflows, and geospatial applications. The ideal candidate combines strong data engineering expertise with experience in knowledge graphs, data quality, and large-scale information management.
Key ResponsibilitiesDesign and develop scalable data ingestion pipelines for structured, unstructured, geospatial, and sensor-based data sources.
Build and maintain batch and streaming data processing systems across cloud, on-premises, and disconnected environments.
Develop integrations with APIs, databases, file systems, enterprise applications, and external data sources.
Design schema mapping, normalization, and transformation processes that support diverse customer data models.
Implement entity resolution, record linkage, deduplication, and data matching capabilities across multiple sources.
Preserve data lineage, provenance, auditing, and traceability throughout the data lifecycle.
Create data validation, monitoring, replay, and exception-handling processes for complex data environments.
Develop workflows for managing ambiguous records, conflicting information, and data quality issues.
Define and measure data quality metrics, onboarding effectiveness, and operational performance indicators.
Support knowledge graph, retrieval, AI, and analytics capabilities through high-quality governed datasets.
Partner with engineering and stakeholder teams to transform recurring onboarding requirements into reusable platform capabilities.
Contribute to platform architecture, engineering standards, and long-term data strategy initiatives.
Additional DetailsFully onsite 5 days a weekFull-time exempt positionHands-on engineering role with substantial ownership and technical influenceOpportunity to work on large-scale data, knowledge graph, and AI-driven initiativesStaff-level candidates may provide architectural leadership, mentorship, and engineering guidanceCandidates must be authorized to work in the United States and satisfy applicable regulatory employment requirements
Role SummaryThe Data & Knowledge Engineer will lead the onboarding, transformation, and governance of complex multimodal data into scalable data and knowledge platforms. This role focuses on integrating structured and unstructured data sources, designing reusable data pipelines, developing entity resolution frameworks, and enabling high-quality data for analytics, retrieval, AI workflows, and geospatial applications. The ideal candidate combines strong data engineering expertise with experience in knowledge graphs, data quality, and large-scale information management.
Key ResponsibilitiesDesign and develop scalable data ingestion pipelines for structured, unstructured, geospatial, and sensor-based data sources.
Build and maintain batch and streaming data processing systems across cloud, on-premises, and disconnected environments.
Develop integrations with APIs, databases, file systems, enterprise applications, and external data sources.
Design schema mapping, normalization, and transformation processes that support diverse customer data models.
Implement entity resolution, record linkage, deduplication, and data matching capabilities across multiple sources.
Preserve data lineage, provenance, auditing, and traceability throughout the data lifecycle.
Create data validation, monitoring, replay, and exception-handling processes for complex data environments.
Develop workflows for managing ambiguous records, conflicting information, and data quality issues.
Define and measure data quality metrics, onboarding effectiveness, and operational performance indicators.
Support knowledge graph, retrieval, AI, and analytics capabilities through high-quality governed datasets.
Partner with engineering and stakeholder teams to transform recurring onboarding requirements into reusable platform capabilities.
Contribute to platform architecture, engineering standards, and long-term data strategy initiatives.
Additional DetailsFully onsite 5 days a weekFull-time exempt positionHands-on engineering role with substantial ownership and technical influenceOpportunity to work on large-scale data, knowledge graph, and AI-driven initiativesStaff-level candidates may provide architectural leadership, mentorship, and engineering guidanceCandidates must be authorized to work in the United States and satisfy applicable regulatory employment requirements
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What they do
A Data Engineer designs, builds and manages the information or big data infrastructure. Develops the architecture that helps analyze and process data in the way the organization needs it. Makes sure those systems are performing smoothly.
$127,645 / year median in California
+3% projected growth