Top Data Analyst Jobs

Support enterprise data warehouse data accuracy and completeness: analyze and resolve data issues, create and load source-to-target mappings, validate ETL code, and consult reporting teams on variances.

The Data Analyst will optimize marketing funnel metrics, conduct analyses, manage dashboards, and promote data-driven decision-making within the team.

Lead data strategy for Stripe's risk product, design metrics and frameworks, manage data reliability, mentor analysts, and evaluate risk experimentations.

The Staff Data Analyst will provide insights to product, marketing, and commercial teams, create visualizations, define metrics, design experiments, and enhance user engagement through data-driven decisions.

Temporary 6-9 month Staff Data Analyst supporting eCommerce and marketing analytics. Lead data-driven projects, define and track metrics, analyze product and web data, build dashboards and automated reports, and provide insights for product teams and brand partners to improve user experience and business performance.

Perform stakeholder interviews and exploratory analysis to surface insights; build dashboards and reports; profile data and assess quality; leverage cloud data platforms; collaborate with engineers and clients; facilitate agile workshops and explore AI/GenAI to accelerate reporting and decision intelligence.

Leads requirements gathering and develops scalable analytics solutions, dashboards, semantic models, and self-service BI products. Partners with Analytics Engineering on Snowflake canonical models, dbt transformations, data quality, testing, and migration from legacy platforms. Applies responsible AI-assisted tools, mentors analysts, establishes standards, coordinates delivery across stakeholders, and drives adoption and business impact.

Own and maintain data products end-to-end for sector teams, analyze large datasets, refine methodologies, automate workflows using AI and tooling, collaborate with Research, Engineering, and Product, and deliver accurate, client-facing insights and improvements.

Develop and support Qlik dashboards, data visualizations, analytical models, and reporting solutions for CBP Trade mission decision-making. Collaborate with stakeholders, product owners, and development teams to refine requirements, support Agile delivery, manage risks, demonstrate analytics products, gather feedback, and improve analytics capabilities and processes.

Lead development and operationalization of enterprise data risk frameworks, KRIs/KPIs, and risk registers. Produce dashboards and reporting, track remediation, partner with data, technology, risk, and compliance teams, and support data protection, governance, and adoption activities across cloud data environments.

The Senior Revenue Operations Analyst will ensure data quality across systems, integrate third-party data into CRM, define quality metrics, and collaborate cross-functionally to improve data processes.

The Senior Revenue Operations Analyst will enhance GTM data quality, integrate 3rd party data into CRM, and solve data issues collaboratively with various teams.

Analyze cellular technology data related to service coverage and user experience. Build business intelligence and analytical datasets, define requirements for additional mobile-app data collection, develop visualization and analytics solutions, present findings to stakeholders, document workflows and data dictionaries, and collaborate with data engineers to optimize data platforms and deliver actionable insights for product development.

Manage master data, users, roles, datasets, reporting environments, and data quality. Generate and troubleshoot reports, support data warehouse requirements, maintain data integrity and normalization, evaluate system updates, and provide technical expertise in data storage, mining, and cleansing. Train end users on reports and dashboards while translating business requirements into clear, nontechnical recommendations.

Build, test, validate, revise, and migrate more than 50 BI reports during a reporting modernization initiative. The analyst will validate SQL-based outputs in Azure SQL and Azure Synapse, reconcile migrated reports with legacy results and source data, investigate discrepancies, and collaborate with business, engineering, architecture, and reporting stakeholders. The role requires strong data-validation skills, stakeholder communication, and independent ownership of reporting deliverables.

Analyze insurance policy, premium, claims, billing, and financial data; build KPI dashboards and reports; write and optimize SQL; validate and model datasets; identify trends, anomalies, fraud indicators, and leakage; and translate business questions into clear recommendations for underwriting, actuarial, claims, finance, and other stakeholders. The role supports pricing, reserving, portfolio management, retention, and loss-ratio analyses.

Gather, clean, and validate data from multiple sources; analyze operational and supply chain data to identify trends and risks; build dashboards and KPI scorecards; automate reporting and data pipelines; support cross-functional teams and leadership with recurring and ad hoc analysis to inform process improvements and decision-making.

Analyzes, cleanses, validates, and prepares operational datasets for mailing, email, reporting, billing, and processing activities. Develops Databricks queries and Alteryx workflows to automate processes and improve data quality. Performs audits, reconciliations, root-cause analysis, and corrective actions while maintaining governance and security compliance. Provides actionable insights, mentors junior analysts, communicates findings, and leads continuous improvement initiatives.

Own Kepler’s transaction data feed end-to-end, ensuring accuracy, improving methodologies, developing QA frameworks, solving complex analytical problems, and prototyping enhancements. Analyze massive datasets, automate workflows with AI, evaluate client-facing AI outputs, address high-complexity customer questions, and collaborate with Research, Product, Data Science, and Engineering teams.

Analyze platform, product, customer, advertising, and operational data to generate actionable insights. Build dashboards, reporting frameworks, automated workflows, and scalable analytics pipelines. Evaluate experiments and analytical methodologies, improve forecasting and data accuracy, and partner with product, engineering, marketing, revenue, and leadership teams to influence strategy, customer experience, and platform growth.

Develop reporting, analytics, metrics, and dashboards to optimize autonomous-vehicle data collection and software development processes. Partner with data scientists, software leaders, and cross-functional stakeholders to prioritize data sourcing, build scalable data pipelines, monitor operational processes, and communicate insights. The role uses on-road and simulation data to support Aurora Driver development and commercialization.

Provides advanced data analysis, reporting, dashboard development, data validation, and information management support for Army medical logistics readiness programs. Analyzes inventory, supply chain, performance, and operational data; creates executive reports and visualizations; troubleshoots information systems; supports data integration, testing, process improvement, SOP development, and strategic decision-making for AMLC leadership.

Collects, organizes, curates, and maintains macroeconomic and market time-series data for systematic investment research. Responsibilities include data sourcing, vendor management, metadata maintenance, historical data cleaning, seasonal and calendar adjustments, diagnostics, quality control, revision-aware dataset management, and exploratory analysis. Works with research analysts to deliver investment-ready datasets across equities, foreign exchange, rates, and commodities.

Supports Army medical logistics readiness programs by collecting, validating, analyzing, and reporting operational, inventory, supply chain, and readiness data. Develops dashboards, scorecards, statistical reports, executive briefings, and KPIs using tools such as Power BI and Excel. Troubleshoots information-system requirements, supports data integration and testing, improves reporting processes, creates SOPs and training materials, and provides actionable insights for logistics planning, resource allocation, and mission readiness.

Analyzes and reconciles data from multiple sources, performs data profiling and quality assessment, creates conceptual, logical, physical, dimensional, and relational models, and documents source-to-target mappings. Develops data visualizations, interprets patterns and trends, supports predictive analysis, identifies master and reference data, and collaborates with data scientists, business partners, data stewards, and architects to ensure governance and data protection compliance.