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 semiconductor materials pricing data, identify market trends, validate and standardize information, monitor data quality, investigate discrepancies, document analyses, and support data pipeline and ETL optimization. The role also involves communicating findings, improving data hygiene, and collaborating cross-functionally while learning new analytical tools and best practices.

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.

Analyzes structured and unstructured data, performs exploratory and statistical analysis, builds dashboards and predictive machine learning models, and communicates insights to stakeholders. The role uses SQL, Python, BI tools, cloud data platforms, distributed processing, and modern AI/GenAI technologies. Responsibilities also include data quality, governance, pipelines, model deployment and monitoring, stakeholder collaboration, and translating analytical findings into business recommendations.

Support execution and adoption of enterprise data governance standards by translating governance decisions into actionable plans, tracking work in JIRA, and delivering executive-ready metrics, dashboards, and scorecards. Perform fit-gap and readiness assessments, analyze complex datasets to surface risks and opportunities, and partner with domain, architecture, platform, and business teams to drive sustained governance adoption and measurable outcomes.

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.

Support data center construction cost planning, forecasting, and controls across project lifecycles. Maintain program-level cost forecasts, prepare estimates and commercial risk assessments, compile benchmarking data, and coordinate with engineering and external cost consultants to optimize capital efficiency and inform location and deployment decisions.

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.

Lead strategic scenario modeling and automation for supply chain planning, linking demand, manufacturing, inventory, capital, and financial outcomes. Provide executive decision support, build scalable reporting and self-service dashboards, partner with IT/data engineering to automate workflows, mentor analysts, and influence cross-functional leaders with data-driven recommendations.

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.

Audit and improve human and model-generated data outputs for accuracy, consistency, and policy compliance. Provide actionable feedback, clarify evolving guidelines, support annotators, coach new team members, monitor workflows and blockers, identify recurring issues and edge cases, participate in calibration discussions, and document findings to improve team performance and quality at scale.

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.

Partner with business teams to convert manual reporting and spreadsheet workflows into trusted, self-serve data products and automated processes. Define metrics, build dashboards, scope and write engineering-ready specs, triage tool requests, and deliver lightweight automation or handoffs to engineering to improve reporting trust, reduce manual work, and increase efficiency.

Partner with business teams to convert manual reporting and spreadsheet-driven workflows into trusted self-serve data products and automated tooling. Define metrics, build or scope dashboards and automation, triage and prioritize tool requests, write engineering-ready specs, and deliver lightweight fixes or handoffs to engineering. Measure success by reduced manual work, trusted dashboards, and time saved.

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.

Design and maintain scalable data pipelines and unified data models for marketing measurement. Build BI dashboards, reporting frameworks, and semantic layers. Implement data governance, quality checks, and anomaly detection. Perform measurement, attribution, forecasting, and audience segmentation. Support AI-enabled and conversational analytics, generate automated insights, and present findings to stakeholders.

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

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.

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 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 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.