Data Analyst

Euromonitor International

. Transform complex data and market information into clear, reliable, and actionable insights for clients worldwide.

Posted 10/15/2026full-timeShanghai • ChinaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in data analysis, validation, and quality management using SQL, Python, and R, while effectively communicating insights to diverse audiences. Proficient in creating visualizations and reports with tools like Power BI and Tableau, and applying data governance principles.

Highest-signal resume keywords

SQL Data ExtractionPython Data AnalysisData Quality ManagementPower BI VisualizationAI Tool Utilization

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data AnalysisData ValidationData Quality ManagementData GovernanceETL ProcessesVersion ControlData CleaningData OrganizationAutomationWeb Scraping

Soft Skills

Analytical SkillsProblem-SolvingCommunication Skills

Tools & Technologies

ExcelSQLPythonRPower BITableauGitAI-Powered ToolsBusiness Intelligence ToolsData Visualization Tools

Industry Keywords

Data AnalyticsData InsightsComplex DatasetsDigital Behavioral DataResearch ValidationAutomation TechniquesDashboardsVisualizationsClient DeliverablesData Pipelines

Tech Stack

Tools & technologies

ETLPythonSQLTableau

About the role

Key responsibilities & impact

Transform complex data and market information into clear, reliable, and actionable insights for clients worldwide.
Work with diverse data sources and support research and validation activities.
Extract, clean, organise, and analyse structured and unstructured data using Excel, SQL, and other relevant data tools.
Use Python or R for data analysis, automation, validation, and repeatable reporting workflows.
Work with large and complex datasets, including web-scraped, digital behavioural, website, database, and third-party source data.
Enrich, validate, and contextualise datasets for client and internal deliverables.
Apply data quality, validation, and governance standards.
Create dashboards, visualisations, reports, and presentations using analytics and business intelligence tools.
Interpret analytical findings and translate them into actionable insights for technical and non-technical audiences.
Support data preparation, transformation, and governance activities.
Maintain organised project files, document assumptions and methodology, and use version control or structured documentation practices.
Collaborate with global analyst, data, research, and client-facing teams to deliver high-quality output on time.
Build capability in data analytics, automation, visualisation, and emerging data science techniques.
Leverage AI-powered tools and automation techniques to improve workflows.

Requirements

What you’ll need

Working knowledge of SQL for extracting, joining, filtering, and validating data from multiple sources.
Working knowledge of Python or R for data analysis, automation, and reporting.
Strong understanding of data analysis techniques, data validation, and data quality management.
Experience working with large and complex datasets such as web scraped data or digital behavioural data.
Ability to build meaningful visualizations, dashboards, and reports using industry-standard tools such as Power BI and Tableau.
Strong analytical and problem-solving skills with the ability to derive actionable business insights from data.
Ability to communicate complex analytical findings to both technical and non-technical audiences.
Understanding of data structures, data pipelines, ETL processes, and data governance principles.
Experience using version control tools (e.g., Git) and applying good coding and documentation practices.
AI literacy, including effective use of AI tools, prompt engineering, automation, and agent-based workflows to enhance research, analysis, and operational efficiency.