Data Engineer Jobs in Irvine, CA

Lead design and implementation of data architecture, ETL/ELT pipelines, data models, warehouses and lakes. Ensure data governance, security, cloud deployments, performance and cost optimization. Coach and manage team members, partner with stakeholders, and drive data-driven solutions for clients.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Design and implement data architecture and scalable ETL/ELT pipelines on cloud platforms (AWS/Azure/GCP). Analyze complex problems, mentor junior staff, ensure data governance/security compliance, liaise with stakeholders, and deliver high-quality client solutions while developing technical and client-facing skills.

Design and build data infrastructure and pipelines using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, collaborate with clients, and apply data architecture, transformation, and analytics to deliver insights.

Lead development and delivery of healthcare AI/GenAI solutions for health systems—architect RAG and agentic workflows, manage global MLOps and model governance, engage executive stakeholders, and drive production-grade use cases across clinical, financial, and operational domains.

Lead data architecture and platform strategy for IHFM products. Solve complex data engineering problems at device-data scale. Define standards for ingestion, modeling, governance, lineage, validation, quality, SLAs, and traceable pipelines. Influence roadmap with product and engineering leadership.

Design and develop AWS-based data platforms, build and maintain ETL pipelines using PySpark, perform data modeling and governance, integrate event-driven systems with Kafka, manage containerized deployments with Docker and Kubernetes, and produce clear documentation while collaborating with stakeholders.

Design, develop, and maintain databases and scalable data pipelines. Build stored procedures, triggers, and ETL processes; perform testing, tuning, security, and data quality work. Collaborate with developers and stakeholders, document architecture, review code, and support reporting and integrations to enable restaurant and customer-facing systems.

Lead QA for software releases, perform manual and automated UI testing, triage and document defects, build lightweight test automation scripts, ensure end-to-end data quality for 3D spatial/point cloud and BIM outputs, and collaborate with engineering and data teams to resolve processing issues and improve pipelines.

Design, build, and scale resilient data pipelines and infrastructure on AWS. Own the data ecosystem using Databricks or Snowflake, write production-quality Python and SQL code, collaborate with cross-functional teams, and prepare data for analysis and product use in a fast-moving startup environment.

The role involves developing scalable data pipelines, automating workflows, optimizing data models, and ensuring data governance while collaborating with various teams.

Design and optimize scalable geospatial data pipelines to convert high-frequency vehicle sensor telemetry into high-fidelity map features. Build map-matching, trajectory smoothing, and sensor-fusion algorithms, apply statistical tests for change detection and map validation, and lead system architecture for low-latency spatial indexing and storage while collaborating with embedded, perception, and cloud teams.

Develop, deploy, and maintain modeling & simulation and AI solutions (from R packages and dashboards to agentic AI workflows) for Data & Statistical Sciences. Architect solutions, run feasibility assessments, create benchmark test sets, iterate on deployed tools, and collaborate with stakeholders to translate requirements into production-ready, reproducible solutions.

Lead architecture and delivery of scalable AWS data platforms and pipelines using Databricks or Snowflake. Build automated Python/SQL ETL, define data models, set code standards, mentor engineers, and drive data strategy across cross-functional teams.

Design, build, and maintain data ingestion pipelines and integrations from intermittently-connected robots to analytics, ML training, and operations. Implement SDKs, connectors, schema contracts, retries, backfills, monitoring, and optimize pipeline performance, scalability, and cost. Collaborate with robotics, autonomy, and deployment teams to ensure reliable end-to-end data delivery and quality.

Build and operate the cloud foundation for the data platform: design compute, storage, and networking; manage IaC and GitOps; provision for large-scale sensor and ML workloads; own reliability, security, observability, cost management, and internal tooling to enable pipeline and analytics teams.

Design and build a scalable data platform and tooling for robotics/autonomy data ingestion, integration, and delivery. Build SDKs, connectors, and APIs (REST/gRPC, webhooks, CDC) to integrate diverse sources and downstream ML/BI systems, ensure schema/versioning/reliability, and optimize pipeline performance, scalability, and cost.