Data Engineer Jobs in Sunnyvale, CA

Design, build, and operate production ML systems that generate trusted signals for ranking, retrieval, recommendations, propensity/churn/LTV, and next-best-action decisioning. Define signal/data contracts, own feature and candidate generation through serving, experimentation, monitoring, and feedback loops, and evaluate long-term business impact, trust, fairness, and compliance. Partner across product, data, modeling, risk, and compliance and apply AI/agents to accelerate engineering and operations.

The AI-Native Data Engineer will build data pipelines, architect databases, design GCP infrastructure, and automate workflows for energy management using AI.

The Staff Business Systems Engineer will manage systems supporting Data Center operations, focusing on capacity planning, lifecycle management, integrations, and asset tracking across infrastructure and finance. Responsibilities include architecture design, data modeling, and ensuring operational compliance.

Design, build, and maintain large-scale GCP data pipelines and data warehouse solutions using Dataproc, GCS, BigQuery, Hadoop/Spark/Hive and Airflow. Mentor engineers, run agile ceremonies, prioritize backlog, provide on-call support, and deliver data models and products at multi-TB/PB scale.

Design, build, and maintain production-grade ETL/ELT pipelines and data models using dbt, Spark, and cloud platforms. Manage ingestion, data quality, observability, semantic layers, and BI outputs. Collaborate with analysts and data scientists to deliver governed, high-quality data products and implement DataOps and CI/CD practices.

Design, build, and maintain scalable data processing pipelines and infrastructure (ETL/ELT). Implement large-scale data processing (Spark, MapReduce, Kafka), support stakeholders with analysis and reporting, ensure secure multi-region data handling, and optimize data delivery for analytics and business insights.

Design and build foundational dimensional data models, enterprise metrics, and curated data products on a modern lakehouse. Partner with business domains to translate processes into scalable, high-quality datasets, optimize analytical workloads, and operate distributed processing systems to support analytics, BI, and AI.

The Founding Data Engineer will manage the company's data models, ensure metric integrity, and work with various teams to deliver reliable metrics and reporting systems.

Lead design, development, and deployment of data reporting and dashboard solutions for Client Service Training. Work with project leadership to create tables/files, run ad-hoc reports, validate results, automate scheduled reports or integrate with dashboard tools, and communicate insights using BI and statistical tools.

Lead and mentor a data engineering team, define technical vision and strategy, oversee data pipeline design, and collaborate with cross-functional teams.

Build, validate, and operate enterprise data connector integrations and ETL pipelines (T1-T3). Maintain data quality frameworks, handle schema/API changes, produce mapping documentation, support MCP endpoint integrations for AI agents, and own production pipeline reliability and onboarding of incoming engineers throughout the engagement.

As a Senior Software Engineer, you'll design and build data models, APIs, and backend services for a complex datacenter infrastructure platform, while ensuring high performance and scalability.

As a Growth Data Engineer, you will build and manage marketing data and attribution systems, ensuring reliable data flow and accurate measurement of acquisition efforts. The role involves collaboration across product, marketing, and data teams with a focus on optimizing campaign performance.

The Founding Data Engineer will design and build OpenArt's core data platform, ensuring data reliability, consistency, and scalability to support leadership and product metrics.

As a Principal Data Processing Engineer, you will enhance a data processing engine, collaborate on open-source platforms, and optimize performance.

Build and operate scalable data ingestion, transformation, and connector frameworks; design and maintain a knowledge-graph-based data fabric; normalize and vectorize enterprise data for LLM/AI workflows; implement governance, lineage, access controls, and secure APIs to serve ML/agent pipelines.

Design and implement high-performance, parallel algorithms in C++ and CUDA to accelerate dataframe and database operations. Contribute to open-source projects (cuDF, Velox, Presto, Spark), profile and optimize code, and collaborate with GPU hardware and software experts to build scalable data-processing libraries.

Lead architecture and implementation of scalable ML data pipelines and tooling to turn autonomy data into training datasets. Build data selection, active learning, inference-at-scale, vector DB management, labeling integration, QC automation, and introspection tools while partnering with ML researchers and infra teams.

As a Senior Data Engineer at TRI, you will design and build robust data infrastructure and pipelines to support autonomy research and simulation workflows.

The Big Data Developer (Spark) will be responsible for Spark and Scala development, Hadoop performance tuning, and SQL coding. Requires extensive experience in data processing and performance optimization.

The Senior Data Analysis Engineer will analyze autonomous driving product performance, improve testing efficiency, automate metric generation, and collaborate with engineering teams to enhance product quality and insights.

The role involves designing and building data pipelines for analyzing user feedback on AI models, ensuring data quality and infrastructure scalability.

The Senior Software Engineer will scale open-source data infrastructure, handle data lifecycle tasks, and support internal and external products.

Build and productionize internal AI-powered tools and data systems. Implement and maintain infrastructure, data pipelines, deployments, monitoring, and access controls. Integrate third-party AI services, ensure data quality, document systems, and collaborate with stakeholders to deliver maintainable solutions.

Develop and enhance the data infrastructure for Waymo's ML models, focusing on data needs, storage efficiency, and integration across various use cases.