Data Engineer Jobs in Sunnyvale, CA

The Data Reliability Engineer will enhance the resilience and scalability of data infrastructure, focusing on automation and reliability. Responsibilities include managing data pipelines, operating Kubernetes clusters, and defining observability standards.

The Senior Staff Physical AI Data Algorithm Engineer is responsible for designing and optimizing a vehicle-cloud data closed-loop architecture, managing data toolchains, and ensuring high-quality data standards throughout the model development cycle.

You will create large datasets and training recipes, develop methods for data mining, create scalable infrastructure solutions, and collaborate with ML infrastructure teams.

Build next generation distributed data storage and processing systems, including projects like Apache Spark and Delta Lake, while focusing on customer value and handling complex data engineering pipelines.

As a Senior Software Engineer at Databricks, you will design and build advanced distributed data storage and processing systems focusing on optimizing performance and supporting various data workloads.

The role involves designing scalable data pipelines for 3D, video, and sensor data, optimizing infrastructure, and productionizing ML models with researchers.

Lead design and implementation of teleoperation and demonstration collection systems, build curation and quality pipelines, source and augment robotic datasets, create tooling for annotation and exploration, and measure downstream impacts on model and policy performance.

As a Software Engineer focused on Data at Speechify, you'll manage data collection and ingestion for model training, enhance cloud infrastructure, and collaborate closely with AI scientists to optimize data quality and cost-efficiency for next-gen products.

The Software Engineer will support data collection for model training, manage the cloud infrastructure, and collaborate on data pipelines to enhance Speechify's AI capabilities.

The Software Engineer will enhance data collection and ingestion pipelines, operate cloud infrastructure, and collaborate on AI datasets for model training.

As a Data Science and Machine Learning Software Engineer at NetApp, you will develop algorithms for real-time personalized search and recommendation using IoT data, while working on cloud-based services and analytics.

As a Software Engineer, you will enhance the data infrastructure by building new concurrency controls, indexing schemes, and optimizing distributed data processing algorithms.

As a Principal Software Engineer in Ads Infrastructure, you'll design and oversee large-scale distributed systems to enhance Unity's advertising platform, ensuring scalability, fault tolerance, and operational excellence.

Design and build scalable, semantically consistent 360 entity data models and transformation pipelines. Implement cleansing, enrichment, KPIs, scoring, and business rules in SQL and Python/Scala, ensure data quality, lineage, and performance at scale. Use AI coding assistants and SDD to accelerate development, create tests and documentation, and collaborate with domain experts, data scientists, and product teams to deliver trusted, reusable data assets.

Build and productionize large-scale data pipelines and platforms to generate ML and evaluation datasets from driving logs and simulation data. Design tools for data mining, exploration, and analysis, and collaborate with Data Science and Quantitative Analytics to deliver high-impact, production-ready infrastructure and dataset generation.

Build and scale AI data and ML infrastructure: evaluation systems, fine-tuning pipelines, agent-first product surfaces, high-throughput data workflows, and integrations of new models into production.

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

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

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.

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 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.

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.

Design and operate petabyte-scale end-to-end data pipelines for autonomous driving: onboard upload, cloud preprocessing, dataset production, and model training input. Build data cleaning, annotation QA, lineage, versioning, metadata management, and high-throughput distributed processing. Optimize I/O, memory, transmission, and containerized deployments; support cross-team collaboration and algorithm iteration.

The principal engineer will lead the development and integration of high-speed data converters, optimize performance, and mentor junior engineers in advanced technologies.

Lead the architecture, design, and implementation of a high-performance data processing engine focused on large-scale data processing.