Data Analyst Jobs in Santa Clara, CA

The Staff Data Analyst will lead data strategy for Compliance, analyzing regulatory engagements, and driving effectiveness through actionable insights and collaboration across various teams.

Analyze enterprise AI initiatives, develop KPIs and executive dashboards, measure AI adoption and business value, and partner with cross-functional stakeholders to inform AI governance, reporting, and strategic recommendations. Design scalable data models and reporting solutions to improve visibility into AI portfolio health and outcomes.

The People Data Analyst role involves analyzing employee data to provide insights on engagement and retention, developing dashboards, and ensuring data integrity for HR reporting.

Manage a portfolio of data center, real estate, network, and equipment leases; ensure lease data integrity and ASC 842/IFRS16 compliance; abstract complex lease agreements into the lease database; coordinate with Accounts Payable and Operations for payments and reconciliations; resolve landlord billing disputes; perform OpEx desk audits; and drive process and reporting improvements.

Early-career data professional responsible for collecting, cleaning, and analyzing data, performing EDA, developing reports and dashboards, supporting basic predictive models, and presenting insights to stakeholders.

Analyze data center operational practices, identify risks and inconsistencies, and create scalable enablement materials (SOPs, runbooks, templates, training). Partner with technicians, engineers, security, and compliance to validate procedures, support audit readiness, and leverage modern tooling including AI/LLM workflows to accelerate documentation and onboarding.

Manage product data and part creation across the product lifecycle for AR/VR hardware. Create/release complex BOMs, manage ECOs and AMLs, support NPI and prototype builds, partner with engineering, supply chain, manufacturing, and program teams, and provide PLM end-user support and governance.

Lead design, build, and maintenance of scalable data pipelines, sandbox databases, and analytics dashboards. Investigate and resolve complex data discrepancies, perform ETL/ELT, data modeling, and performance tuning using Databricks, Starburst, Kafka, SQL, and Python. Partner cross-functionally, enforce data governance, document processes, and mentor team members to support research prototyping and business insights.

Support D2C and B2B growth by building automated dashboards, performing funnel and conversion analyses, tracking lifecycle marketing and ad performance, and partnering with cross-functional teams to scale growth initiatives. Learn from mentors and progress into owning growth and marketing analytics domains.

The role involves managing the product lifecycle, coordinating with R&D and marketing for new product development, and enhancing product data automation.

Research, evaluate, and manage partnerships with data providers. Assess datasets for coverage and interoperability, support deal structuring, maintain partnership pipeline, and collaborate with product, engineering, and legal to integrate data into the platform.

Annotate and label images and video from humanoid robots using proprietary tools, collaborate with ML engineers on guidelines, flag edge cases, maintain quality and throughput, and provide feedback to improve workflows.

Lead hands-on analytics and a small team to improve eBay's shipping ecosystem using advanced analytics, AI, experimentation, and predictive modeling. Build models, simulations, data pipelines, dashboards, and run A/B tests to optimize managed shipping, carrier routing, delivery performance, and label adoption. Partner with Product, Engineering, Finance, and business teams to translate insights into measurable operational and business outcomes.

The role involves supporting the Finance department through analytical reporting, data management, and collaboration with IT to ensure data accuracy and reliability using tools like Power BI and Tableau.

Lead master data governance and business analysis for product/material data across Agile PLM, SAP MDG and S/4HANA. Define governance, steward data, design MDG workflows and integrations, drive data migration/cleansing, perform impact analysis, support cross-functional stakeholders, and champion data quality improvements.

The Robot Data Operations Analyst will control robots, evaluate performance, provide quality assurance, and document observations safely in an R&D setting.

Audit and review data labeling outputs, provide actionable feedback, train and support labeling teams, monitor workflows, identify recurring issues and edge cases, participate in calibrations and stakeholder syncs, and help improve guidelines and processes in human-in-the-loop AI workflows.

Audit and ensure quality of data labeling outputs, coach and onboard Data Labeling Associates, provide actionable feedback, monitor workflows, identify patterns and edge cases, and help improve guidelines and processes in human-in-the-loop AI workflows.

Audit and validate data labeling outputs, provide structured feedback and hands-on training to annotators, monitor workflows and escalate issues, help apply and improve guidelines, and identify patterns in human and model outputs to maintain high-quality AI training data.

Audit and ensure quality of labeled data by reviewing DLA outputs, providing feedback and coaching, supporting onboarding and training, monitoring workflows, identifying recurring issues and edge cases, and contributing to guideline and process improvements in human-in-the-loop AI workflows.

Audit and improve data labeling quality in human-in-the-loop ML workflows. Coach and onboard labelers, provide actionable feedback, monitor queues, identify recurring issues, and help refine guidelines and processes.

Audit and ensure quality of data labeling outputs, coach and onboard annotators, enforce and improve guidelines, identify recurring issues and edge cases, escalate risks, and document feedback to support human-in-the-loop AI workflows.

Audit and ensure quality of data labeling outputs, coach and onboard annotators, apply and refine guidelines, monitor workflows and escalate issues, document findings, and support human-in-the-loop AI evaluation processes.

Audit and monitor data labeling outputs, provide actionable feedback, support onboarding and training of annotators, enforce and improve guidelines, escalate workflow issues, and document findings to maintain high-quality human-in-the-loop AI data processes.

Audit and ensure quality of data labeling work for ML using human-in-the-loop processes. Provide feedback, train and support annotators, monitor workflows, identify recurring issues, and help improve guidelines and processes.