Official ATS Resume & Keywords Guide
Data Analyst Resume & ATS Keyword Guide
Format your Data Analyst resume to highlight SQL, Python, Tableau, PowerBI, statistical modeling, and business intelligence impact.
Recommended Resume Structure
- 1Header: Name, Email, LinkedIn, GitHub / Kaggle Profile
- 2Core Skills: SQL, BI Tools, Analytics & Statistics, Programming, Data Pipelines
- 3Professional Experience: Business ROI, automated dashboards, statistical insights
- 4Analytics Projects: End-to-end data pipelines and visualization dashboards
- 5Education: Statistics, Mathematics, Computer Science, or Economics
High-Intent ATS Keywords for Data Analyst
Must-Have Technical Keywords (35% Weight)
SQLPythonExcel (Advanced)TableauPower BIData VisualizationData ModelingETL Pipelines
Preferred / Bonus Keywords (30% Weight)
Pandas / NumPySnowflakedbtGoogle AnalyticsA/B TestingStatistical AnalysisBigQuery
Google X-Y-Z Bullet Point Optimization Examples
Weak / Generic Bullet:
"Built sales reports and analyzed customer data."
FAANG-Grade ATS Bullet:
"Engineered automated PowerBI dashboard connected to Snowflake, identifying ₹1.2M in annual customer churn prevention opportunities."
💡 Links data visualization tools to tangible business revenue and retention outcomes.
What Recruiters Look For
- •Advanced SQL skills (Window functions, CTEs, complex joins)
- •Ability to translate raw data into actionable executive decision insights
- •Experience with modern cloud data warehouses (Snowflake, BigQuery)
Common Screening Mistakes
- •Listing generic Microsoft Excel without highlighting advanced functions or SQL
- •Failing to quantify the business outcome of data analysis projects
Frequently Asked Questions
Should a Data Analyst know Python or R?
Python (Pandas, NumPy) is preferred by 80%+ of recruiters for data manipulation and automation.
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