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Technology · Mid Level

Data Analyst Resume Example

Data analyst resumes need to bridge technical skills and business outcomes. Hiring managers want to see that you can query data AND communicate insights that drive decisions.

Full Example Resume
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A
Analyst Sample
Data Analyst
candidate@example.com
+1 (555) 123-4567
San Francisco, CA
linkedin.com/in/data-analyst
Skills
SQL
Python
Tableau
Excel
Power BI
dbt
Profile

Data analyst with 4 years building dashboards and driving data-backed decisions at GrowthCo. Automated 12 weekly reports saving 20 hours/week across 4 departments. Expert in SQL, Tableau, and Python (pandas).

Experience
Data Analyst
GrowthCo
Jan 2023Present
Built executive dashboard in Tableau tracking 18 KPIs, used weekly by C-suite in strategy reviews
Automated 12 weekly reports using Python scripts, saving 20 hours/week across 4 business units
Identified $340K in recoverable revenue through customer churn analysis, enabling targeted win-back campaign

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Sample Professional Summary

Data analyst with 4 years building dashboards and driving data-backed decisions at GrowthCo. Automated 12 weekly reports saving 20 hours/week across 4 departments. Expert in SQL, Tableau, and Python (pandas).

Use this as a starting point — customise it with your own metrics and experience.

Sample Work Experience Entry

Data AnalystJan 2022 – Present
GrowthCo
  • Built executive dashboard in Tableau tracking 18 KPIs, used weekly by C-suite in strategy reviews
  • Automated 12 weekly reports using Python scripts, saving 20 hours/week across 4 business units
  • Identified $340K in recoverable revenue through customer churn analysis, enabling targeted win-back campaign

What to Include in a Data Analyst Resume

  • SQL proficiency level and databases used (PostgreSQL, BigQuery, Snowflake)
  • Visualization tools: Tableau, Power BI, Looker, Metabase
  • Programming: Python (pandas, NumPy) or R
  • Business impact: decisions informed, cost savings, efficiency gains

Expert Tips for Data Analyst Resumes

Tip 1

Be specific about SQL: name the databases (PostgreSQL, BigQuery, Snowflake, Redshift)

Tip 2

Show dashboard adoption: who uses them, how often, what decisions they inform

Tip 3

If you automate reports, show the time savings — it demonstrates clear ROI

Tip 4

Include a link to a public Tableau profile or portfolio if you have one

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