Top Data Analyst Jobs

Lead discovery workshops, author testable user stories, document end-to-end workflows and data lineage, define/enforce data standards and stewardship, own data dictionary, validate data readiness before go-live, identify regulatory data obligations, participate in Data Governance Council, and serve as the business systems analyst for CRM platforms.

Lead cross-functional analyses and build scalable reporting for go-to-market teams. Develop and automate data pipelines, create interactive dashboards, improve data quality, and translate complex findings into actionable recommendations for stakeholders and executives.

Lead development and delivery of BI dashboards and reports, architect scalable BI systems, ensure data quality and governance, perform advanced analysis and forecasting, provide strategic recommendations, establish standardized data models, mentor junior analysts, and communicate insights to stakeholders to inform business decisions.

Process, validate and QA large survey datasets; produce datasets, tables, codeframes and documentation; support weighting, testing and statistical analyses; learn and apply Python/R, automation and AI-assisted tools; improve automated processing workflows under senior guidance.

Senior data processing analyst responsible for end-to-end survey data processing: specifications, weighting, QA, documentation and deliverables. Produce datasets and tables, perform statistical tests, and modernise/automate workflows (Python/R, replace SPSS). Apply AI-assisted tools, act as technical lead for projects, and mentor junior analysts.

Work with data scientists, engineers, and BI developers to deliver end-to-end data solutions using the modern data stack. Build reports, dashboards, KPIs, and ad-hoc analyses; support data modeling, validation, governance, and ML model tuning to inform business decisions.

Lead business analysis for strategic initiatives, driving data-driven decisions, solution design, and cross-functional partnerships. Mentor teams, develop analysis approaches, research process improvements, and ensure solutions meet business objectives within a hybrid, limited-tenure role.

Senior Business Analyst specializing in advanced data visualization: create dashboards, choose optimal chart types for varied audiences, visualize high-dimensional data, apply statistics and financial modeling, collaborate with UX, and help drive execution.

Maintain data dictionary and lineage; design logical and physical data models; map attributes to source documents; validate data quality; support data governance and compliance; collaborate with BI and analysts to enable reporting and Tableau dashboards.

Analyze and consolidate disparate data sources, document functional specifications, review logical and conceptual data models, gather business requirements, validate implementations, support production deployments, investigate data quality issues, and coordinate with technology leads to resolve data completeness and accuracy gaps.

Lead reconciliation data analysis for cash, stock and position records. Gather requirements, document functional specs, validate solutions, support production deployments, investigate data quality and work with technology leads to ensure data completeness and lineage.

Design, build, and maintain interactive dashboards and visual products that translate complex operational and cybersecurity data into clear insights. Collect requirements, create mockups, automate analytics, and produce metrics for patching, vulnerability, and compliance to support executive and operational decision-making.

The Data Quality Analyst audits and standardizes data from various internal sources to ensure accuracy. Responsibilities include developing reports, building data pipelines, and collaborating with teams to manage data integrity.

Analyze C&DS project data to produce actionable insights. Build data pipelines, reports, visualizations and predictive/prescriptive models. Collaborate with IT, data governance, and business stakeholders to enable data-driven decision-making, support reporting needs, and ensure data quality and access.

The Data Quality Analyst will validate data accuracy, develop automated testing frameworks, analyze discrepancies, and collaborate on data governance with stakeholders.

Lead master data governance for product/material domains across Agile PLM and SAP S/4HANA/SAP MDG. Define governance, document requirements and processes, support MDG design and integrations, drive data migration/cleansing, perform impact analysis, and champion data quality across supply chain, manufacturing, and IT stakeholders.

Own and QA high-impact retail data products: design and run QA, investigate and resolve complex data quality issues, collaborate with Insights and Engineering, improve automation and product reliability, and communicate methodology and limitations to clients.

The Senior Analyst will contribute to data enablement, enhance data access, develop strategic data sets, and support analytics solutions while collaborating with stakeholders to improve overall data management and governance.

The Senior Data Analyst - Compliance will support data governance by mapping data lineage, creating policies, and responding to regulatory inquiries.

Own end-to-end analysis of payments, chargebacks, and user lifecycle to identify drivers of net loss. Deep-dive into fraud cases, design and evaluate A/B experiments and risk-rule changes, build monitoring dashboards, partner with Risk, Payments, and Product to convert insights into mitigations, and run ad-hoc analyses of emerging loss trends.

Maintain and manage master data (customer, supplier, product); analyze data quality and perform profiling; support data cleansing, migration, integration, and MDM initiatives; collaborate with IT and business teams; and develop training and user support for MDM processes and tools.

Support enterprise data governance by documenting end-to-end data lineage, designing ADS components, building GCP data pipelines and data quality controls, contributing to data modeling and target-state design, and acting as a bridge between engineering, enterprise architecture, and business stakeholders while presenting findings to senior leadership.

Partner with senior leaders across Marketing, Sales, Product, and CX to analyze data, identify opportunities, build dashboards, run experiments, and deliver data-driven recommendations that drive business growth and operational improvements.

Partner with senior leaders across marketing, sales, product, and CX to identify opportunities, analyze data, produce data-driven recommendations, build dashboards and tools, run experiments, and implement initiatives that grow the business.

Support collection, analysis, interpretation, and presentation of education and workforce data. Conduct descriptive and applied statistical analyses, build visualizations and dashboards, communicate findings to stakeholders, and collaborate across teams to inform decisions and improve student outcomes.