Resume Heat Map for Data Analysts
Data analyst resumes often bury impact in technical details. Use a free heatmap preview to see what stands out—then optimize for clarity and outcomes.
What recruiters look for
- SQL proficiency: Non-negotiable. Show it in context, not just a skills list.
- Business impact: Decisions influenced, revenue affected, time saved.
- Visualization skills: Tableau, Looker, Power BI—whichever matches the role.
- Communication: Can you explain insights to non-technical stakeholders?
Scan-friendly tips
Lead with business outcomes
Start bullets with impact: revenue, time saved, decisions influenced. Technical details come second.
Show tool proficiency in context
"Built SQL pipelines" beats "Proficient in SQL" every time.
Quantify everything
Rows processed, hours saved, accuracy improved—numbers make claims believable.
Match the job description
If they want Tableau, mention Tableau. If they want Python, show Python projects.
Example bullet rewrites
Key skills to highlight
Always include:
- SQL (queries, joins, window functions, CTEs)
- Python or R (pandas, numpy, statistical libraries)
- Visualization (Tableau, Looker, Power BI, or matplotlib/seaborn)
- Excel (pivot tables, VLOOKUP, data modeling)
Include if relevant:
- Statistical analysis (A/B testing, regression, hypothesis testing)
- ETL tools (Airflow, dbt, Fivetran)
- Cloud platforms (BigQuery, Redshift, Snowflake)
- Machine learning basics (if the role requires it)
Data analyst resume tips
Occasional emails with examples, checklists, and new guides. No spam.
Related resources
Quantify achievements
Make your analytical work undeniable with numbers.
Resume summary
Write a technical summary that scans fast.
Resume keywords
Include the right technical terms without stuffing.
For software engineers
If you're more on the engineering side.