Data Engineer Jobs in Sunnyvale, CA

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.

As a Full-Stack Engineer at Labelbox, you will develop and maintain AI tools, focusing on data training systems, intermediate user interfaces, scalable architectures, and work in a collaborative, fast-paced environment.

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

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.

Own and develop concurrent C++ backend services for Webviz to stream time-series and sensor data, integrate offboard storage and WebRTC, optimize latency and throughput, build APIs for automated triage/evaluation, plan technical roadmaps, and mentor engineers.

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

Design and implement high-performance, scalable storage systems and client libraries for AI workloads. Build data loading, checkpointing, caching, POSIX-style and object-store integrations, observability and telemetry, and validate performance with platform, SRE, and AI teams using modern engineering practices.

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 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.

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.

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

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.

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.

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

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

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.

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

Own and scale streaming Kafka pipelines and large-scale Spark batch jobs processing billions of rows. Drive pipeline reliability, observability, data modeling, and cost/latency optimizations. Partner with data scientists and platform engineers, define SLOs, improve efficiency, contribute to shared infrastructure (Airflow, libraries, data catalog), and mentor junior engineers.

The Principal Software Engineer will oversee technical readiness for NVIDIA's GT data generation, resolving upstream blockers and ensuring quality across sensors and data platforms while collaborating with teams in the US and China.

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