Data Analyst Jobs in Santa Clara, CA

Own data center OpEx and power planning, forecasting, budgeting, variance analysis, financial reporting, scenario modeling, and cost optimization. Build complex operational and financial models, develop dashboards, and provide actionable insights to executive leadership. Partner cross-functionally with data center operations, capacity planning, power and sustainability, and sales teams to support strategic decisions and business growth.

Develop and maintain finance data solutions using SQL, Python, AI, BI tools, and financial reporting standards. Automate finance processes with AI agents, transform operating expense, capital, headcount, and purchase order data, and produce reporting and analysis. Monitor data quality, resolve issues, ensure scalable and secure solutions, and collaborate across teams on process optimization, automation, and cost reduction.

Own product analytics for the Accounts Payable product, setting the analytics agenda, defining metrics and OKRs, identifying product opportunities, and influencing roadmap decisions. Responsibilities include experimentation, causal inference, executive reporting, production-grade dbt models, data quality validation, documentation, and AI-assisted workflow automation. The role partners closely with Product, Engineering, and AP leadership and requires confidently presenting insights to senior stakeholders.

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 supply chain business processes and large datasets to identify gaps, improvement opportunities, and actionable insights. Build data visualizations, present findings, catalog data sources and metrics, and support integrated data architecture. Automate complex processes to streamline operational workflows and improve data-driven decision-making.

Owns Simbe’s product data management and Arena PLM administration for robotic hardware programs. Responsibilities include authoring and driving ECOs, MCOs, and deviations through approval; maintaining item masters, BOMs, approved vendor lists, part lifecycles, and documentation integrity; enforcing revision, numbering, and change-control standards; and coordinating implementation with Engineering, Operations, Supply Chain, suppliers, and contract manufacturers.

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.

Updates machine learning training and test datasets, refines annotation guidelines, initiates model training, and evaluates model performance. The role annotates synthetic text and image data, conducts manual quality analysis, identifies error patterns, reports anomalies, and produces findings on utterance quality, LLM evaluation, ASR bugs, and customer pain points. It also applies basic NLP and linguistic knowledge to ensure data accuracy and consistency.

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.

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.

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.

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.