Data Engineer Jobs in Irvine, CA

Design, build, and scale TaxRise’s data infrastructure on AWS using Databricks. Own end-to-end pipelines, ETL/ELT processes, data modeling, orchestration, governance, cluster optimization, and delivery for reporting and analytics. Collaborate with the Chief Data Officer, Salesforce developers, data engineers, and full-stack developers to establish platform standards and support business growth.

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.

Designs, builds, tests, and maintains scalable data pipelines, architectures, data products, and transformation processes supporting clinical development modeling and analytics. Collaborates with statisticians, data scientists, IT, and business stakeholders to develop reusable data solutions using cloud and AI tools. Ensures data quality, automation, regulatory compliance, and adherence to clinical development standards while exploring new technologies and improving pipeline capabilities.

Build and operate scalable data-platform systems for multimodal robotics and machine-learning datasets. Responsibilities include ingestion, processing, validation, labeling, dataset generation, metadata, lineage, versioning, data quality, observability, and workflow reliability. Partner with ML, robotics, infrastructure, and labeling teams to create reusable platform capabilities supporting large-scale data processing, reprocessing, backfills, training, and evaluation.

Build and automate data-flywheel systems for autonomous robots, converting large-scale robot experiences into high-quality, versioned training datasets. Responsibilities include data processing, filtering, labeling, auto-labeling, offline inference, hard-example selection, validation, reproducible dataset generation, and incremental training-data pipelines. Partner with researchers and platform teams to productionize experimental workflows and improve the cycle from robot deployment to usable ML data.

Modernize and maintain Magnus and Goliath platforms across Java, Go, and JavaScript. Build AI-powered features (LLMs, tool-calling), integrate BigQuery, GCP, MySQL and internal APIs, diagnose production issues, write automated tests, and own projects end-to-end from design through deployment and support.

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.

Owns production data-platform components end to end, including ETL pipelines, data modeling, quality checks, monitoring, recovery, and cost optimization. Builds Spark on EMR and Airflow workflows, CDC ingestion, dimensional warehouse layers, and OLAP datasets. Partners with analysts and stakeholders to deliver reliable analytical data while tuning performance and automating reusable platform components.

Build and maintain marketing data pipelines, replace spreadsheet workflows with structured databases, automate data cleaning/deduplication and syncing, develop AI-driven reports and dashboards, and collaborate with marketing, AdOps, and engineering to ensure reliable, unified, AI-ready marketing data.

Design, build, and maintain scalable data pipelines and architectures (ETL, data lake, MDM) using Snowflake and Talend Cloud. Ensure data quality and governance, enable AI-readiness, pilot AI/ML proofs-of-concept, support reporting (Tableau/Power BI), and manage data operations and external vendors.

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, 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.

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.

Design, deploy, and maintain global data platform infrastructure with emphasis on multi-region Databricks orchestration. Lead system architecture, optimize Databricks (Delta, Spark, Unity Catalog), implement IaC with Terraform, build CI/CD pipelines, troubleshoot platform issues, and collaborate with cross-functional teams to meet technical, governance, and performance requirements.

Early-career role to build, operate, and improve cloud data/analytics platforms (Fabric, Snowflake, Databricks). Support platform operations, CI/CD for analytics assets, onboarding for BI tools (Power BI/Tableau), runbooks, monitoring, incident response, and basic security/governance. Work under senior mentorship and contribute to automation, deployment templates, and performance triage.

Lead architecture, operation, and improvement of cloud data and analytics platforms (Fabric, Snowflake, Databricks). Own CI/CD for data assets, BI delivery (Power BI/Tableau), reliability, monitoring, incident response, security, and governance. Enable teams through standards, runbooks, and onboarding; troubleshoot performance and ensure production stability.

Design, build, and maintain scalable Python-based ETL/ELT data pipelines and Airflow workflows implementing Medallion (Bronze/Silver/Gold) Lakehouse patterns. Ensure data quality, performance tuning, monitoring, CI/CD, and cross-team collaboration to support analytics, reporting, and ML use cases while adhering to governance and security standards.

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.

Design, build, and maintain production data pipelines and infrastructure for robot telemetry, logs, sensor data, and events. Implement ingestion, transformation, and orchestration (Airflow), backend services/APIs, and AWS-based storage/processing. Improve reliability with monitoring, retries, schema validation, and data quality checks. Collaborate with robotics, ML, and deployment teams to scale data systems for fleet operations.