Data Engineer Jobs in Santa Clara, CA

Lead diverse technology projects and a team to create solutions for regulatory needs, leveraging distributed microservices and collaboration with product managers.

Build and maintain production-grade ETL/ELT pipelines for large supply-chain datasets (wafers, memory, assemblies). Ensure data quality, curate datasets, design optimized schemas, and enable downstream ML/AI models. Collaborate with procurement, operations, engineering, and IT to centralize legacy workflows and feed unified forecasting systems.

Lead design and optimization of data models and pipelines for compliance and risk; standardize metrics and documentation; build data quality, lineage, and monitoring (including AI agents for automation); manage ETL scheduling, on-call pipeline support, and collaborate with product and non-technical partners to translate business needs into automated, production-ready data solutions.

Design, operate, and maintain flight test data systems for structural loads measurement; develop and validate loads equations, process large flight datasets, build automated pipelines, produce fatigue and loads spectra, compare test data to models, support stress and damage tolerance analysis, and compile certification deliverables while guiding instrumentation strategy.

Lead MLOps engineering for edge and cloud pipelines that ingest and label video for perception models. Build optimized data pipelines, scale labeling and annotation, integrate foundation models for automation, apply software- and hardware-in-the-loop testing, and collaborate with DoD stakeholders to meet field requirements.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

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.

Lead development of AI and ML solutions for healthcare systems, overseeing teams, driving use case development, and ensuring operational excellence while managing global delivery operations.

As a Cloud Data Engineer, you'll build and maintain data pipelines, evaluate new technologies, and enhance AI outcomes. You'll collaborate with data scientists and develop applications in cloud environments using big data technologies.

The Software Engineer will develop and manage data platforms for CoreWeave, focusing on performance, security, and scalability while facilitating data access and compliance with regulations.

Design and implement data platforms, manage data infrastructure, develop streaming architectures, improve performance, and ensure data compliance.

The Data Engineer will process raw data, develop predictive models, and conduct statistical analysis to support business decisions, collaborating with engineering teams and business partners.

The Data Engineer will gather and process large datasets, develop algorithms, conduct data analysis, and improve predictive models for business decisions.

The Data Engineer will gather and process data, analyze trends, support business decisions, and collaborate on predictive models while improving algorithms and efficiency.

The role involves designing and developing data applications, working with large data sets, and requires expertise with various data processing technologies. Candidates should have strong analytical skills and experience in prototyping software applications.

Design, build, and scale high-volume data pipelines and architectures. Lead end-to-end data projects, improve feature engineering and models, ensure data quality and security, perform code reviews, and collaborate with data scientists and business stakeholders to deliver actionable insights.

Design and evolve global compute and storage architecture for large-scale GPU training and inference across multi-cloud and data centers. Enable petabyte-scale data federation, cross-region GPU job execution, advise leadership on cloud strategy, and provide technical leadership and mentorship to advance AI model development and deployment.

Design and implement test automation for instrument software, data pipelines, cloud analytics, and AI/ML outputs. Build data validation frameworks, schema and pipeline checks, integrate tests into CI/CD, validate ELN/LIMS interoperability, ensure traceability and regulatory Quality System compliance, and contribute to test solution architecture and orchestration.

The role involves leading developer relations for AI platforms, guiding partners on product integration, and fostering collaboration for ecosystem growth.

The Data Engineer will design, develop, and maintain scalable data systems, focusing on AWS and big data technologies to support data-driven decision-making and ensure data security.

Build and maintain large-scale data collection and preprocessing pipelines for NLP research. Develop web crawlers, APIs, and workflows; refine LLM outputs into structured datasets; collaborate with researchers to ensure data quality and document methodologies. Support scalable storage, retrieval, and distribution of datasets.

Design and implement scalable data infrastructure and production data transformations. Lead and mentor a small Data Engineering team, ensure quality delivery, collaborate with Product, Data Analysts, and Data Scientists to operationalize algorithms and build robust data repositories.

Build and automate large-scale ML data pipelines and tooling for autonomous trucking. Improve dataset curation, deduplication, labeling, evaluation, and metrics infrastructure. Collaborate with robotics, autonomy, and infra teams to support continuous learning, deployment, and scalable AI infrastructure for Kodiak's fleet.

Lead design and evolution of Archer's data warehouse/lakehouse architecture, define modeling and governance standards, partner with stakeholders to build reusable data models, optimize storage and compute, and maintain production-grade, reliable ETL pipelines.

Seeking Data Platform Engineers to design, build, and manage scalable data pipelines and analytic query engines while ensuring data integrity and performance optimization.