Data Engineer Jobs in Santa Ana, CA

Design, develop, and maintain SSRS reports and Power BI dashboards; perform data modeling and DAX calculations; support ETL (SSIS) and validate data across EMR/billing/CRM systems; gather and translate stakeholder requirements; liaise with offshore teams; perform testing, documentation, and ensure HIPAA/PHI compliance and data governance.

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.

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.

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.

Responsible for assessing and improving data quality. Collaborates with developers to implement data logic, conducts quality reviews, and communicates issues to resolve data quality problems. Provides support to ETL teams and manages customer requirements throughout the project lifecycle.

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.