Data Engineer Jobs in Glendale, CA

Design, build, and scale streaming and batch data pipelines, embedding workflows, and vector store integrations to support AI applications. Implement AI-optimized data models, ensure observability and data quality, and collaborate across infra, ML, and product teams while mentoring engineers and delivering production-ready, reliable data foundations.

Design, build, deploy, and operate scalable cloud data pipelines and warehouse solutions to provide trusted security data. Lead platform architecture, implement IaC and DevOps practices, enforce engineering best practices, and partner cross-functionally to deliver data capabilities supporting security initiatives.

Lead enterprise data governance for Disney's Data Unification initiative: define and enforce policies, embed governance in semantic models and federated platforms, ensure security/privacy/compliance, implement metadata/lineage/quality strategies, support semantic data products and AI governance, and drive adoption and reporting.

Lead design, development, and governance of enterprise ontologies, semantic layers, and knowledge/ entity graphs. Implement graph and vector databases, enable LLM-augmented search and federated data access across Snowflake, Databricks, PostgreSQL, MongoDB, S3, and Kafka. Drive data cataloging, security models, ontology governance, and mentor teams to translate business goals into ontological solutions.

Lead development teams in creating scalable data platforms, focus on ETL/ELT pipelines, data architectures, mentoring junior engineers, and ensuring project alignment with business goals.

The Lead Software Engineer will design, develop, and support scalable cloud-based messaging and integration platforms, provide technical leadership, and ensure performance and reliability across platforms, primarily using Java, Spring Boot, and AWS services.

Lead design, build, and operate scalable, low-latency data systems and platform services for real-time personalization and recommendations. Partner with ML, product, and platform teams to deliver feature serving, inference integration, APIs, monitoring, and reliability. Provide architecture leadership, mentor engineers, and establish operational standards for data pipelines and ML workflows.

Design, build, and operate scalable AWS and Snowflake data pipelines and data products to support reporting, analytics, machine learning, and operational decision-making. Develop curated datasets, data models, and complex transformations; troubleshoot distributed systems; ensure security, testing, and reliability; and partner with business stakeholders across Disney Parks in an Agile environment.

Design, build, and scale streaming and batch data pipelines and embedding workflows; integrate vector stores and AI platform services; implement observability, data quality, and governance; mentor engineers and lead production-ready AI data foundations supporting ad technology.