Data and Knowledge Engineer

Job Description

Job Description

Data & Knowledge Engineer

Company Overview

A 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 Summary

The 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 Responsibilities

• Design 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 Details

• Fully onsite 5 days a week
• Full-time exempt position
• Hands-on engineering role with substantial ownership and technical influence
• Opportunity to work on large-scale data, knowledge graph, and AI-driven initiatives
• Staff-level candidates may provide architectural leadership, mentorship, and engineering guidance
• Candidates must be authorized to work in the United States and satisfy applicable regulatory employment requirements

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Statistics, Information Systems, or a related field, or equivalent practical experience.
• 7+ years of experience building and operating production data platforms supporting structured and unstructured data workloads.
• Strong Python and SQL expertise with modern software development best practices.
• Experience with data ingestion, data integration, entity resolution, record linkage, master data management, or related disciplines.
• Hands-on experience building batch and streaming data pipelines using modern data processing technologies.
• Experience with workflow orchestration, job scheduling, and reliable reprocessing of large-scale data workloads.
• Knowledge of knowledge graphs, vector databases, relational databases, and modern analytical data platforms.
• Experience applying AI or large language models to document processing, data extraction, schema mapping, or data quality workflows.
• Strong understanding of data governance, lineage, provenance, quality controls, and operational monitoring.
• Ability to work with complex, messy, evolving, and ambiguous datasets while maintaining high data quality standards.
• Excellent written and verbal communication skills.

Preferred Qualifications (Nice-to-Haves)

• Experience with OCR, document understanding, table extraction, multimodal processing, or intelligent document automation.
• Experience working with geospatial data, spatial analytics, mapping technologies, or sensor-based datasets.
• Knowledge of ontology development, graph data modeling, knowledge representation, or semantic technologies.
• Experience with active learning, human-in-the-loop review processes, confidence scoring, or data quality automation.
• Familiarity with data lineage, privacy-focused architectures, data contracts, and governance frameworks.
• Experience supporting secure, air-gapped, edge, or highly regulated environments.
• Experience working directly with enterprise, government, or large-scale organizational data onboarding initiatives.
• Background in defense, intelligence, logistics, public sector, public safety, or other complex data-intensive industries.
• Experience mentoring engineers and establishing data engineering standards and best practices.

Compensation & Benefits

• $200K-$300K + discretionary bonus
• Performance-based bonus opportunities
• Comprehensive medical, dental, and vision coverage
• Retirement savings program
• Generous paid time off and company holidays
• Professional development and continuing education opportunities
• Opportunity to work with cutting-edge AI, analytics, and data platform technologies