Should I include BI tool names like Tableau and Power BI?

Yes. Recruiters and ATS filters often rely on tool keywords. Include what you used and reference it in bullets.

Do I need dbt and a warehouse listed?

If the JD mentions them, yes. dbt, Snowflake, and BigQuery are common screening terms.

What metrics help most on a BI resume?

Revenue, churn/retention, funnel conversion, and business-specific KPIs you improved or standardized.

Where do keywords matter most?

Bullets. Show the keyword in context with an outcome, not only in a skills list.

Resume Keywords for BI (Business Intelligence) (ATS-Ready List)

A practical, ATS-ready list of BI keywords recruiters expect: SQL, dashboards, data modeling, ETL/ELT, governance, and decision impact.

Browse more roles in the Resume Keywords hub or generate a custom list with Keywords Finder.

How recruiters scan BI resumes

They scan for SQL strength and how you built reliable datasets, not just charts.
They look for modeling terms: dimensional modeling, metrics layers, definitions, governance.
They check tooling: Power BI/Tableau/Looker plus warehouse (Snowflake/BigQuery) and dbt.
They skim for stakeholder impact: exec dashboards, weekly business reviews, adoption.
They want outcomes: faster reporting, fewer disputes, churn/retention insights, revenue attribution.

Common ATS mistakes in BI

Saying “built dashboards” without naming the business KPI or decision supported.
Missing core keywords from JDs (dbt, Snowflake, BigQuery, semantic layer, governance).
Only listing tools without showing what you modeled or automated.
No mention of data quality, definitions, or reliability.
Bullets lack measurable impact (time saved, adoption, accuracy, revenue insights).

Copy The List

Core Skills

SQL
Dimensional Modeling
ETL/ELT
Metrics Definitions
Data Quality
Dashboard Design
Cohort Analysis

Tools / Tech

SQL
dbt
Snowflake
BigQuery
Tableau
Power BI
Looker
Airflow
Fivetran

Metrics & Action Verbs

MRR
ARR
ARPU
Churn
Retention
Funnel Conversion
Forecasting
Modeled
Instrumented
Automated
Standardized
Visualized

Copy for AI tools

Paste this into ChatGPT, Claude, or any AI writing tool along with your resume for targeted rewrite suggestions.

[BI (Business Intelligence)] Resume Keywords
How recruiters scan:
  - They scan for SQL strength and how you built reliable datasets, not just charts.
  - They look for modeling terms: dimensional modeling, metrics layers, definitions, governance.
  - They check tooling: Power BI/Tableau/Looker plus warehouse (Snowflake/BigQuery) and dbt.
  - They skim for stakeholder impact: exec dashboards, weekly business reviews, adoption.
  - They want outcomes: faster reporting, fewer disputes, churn/retention insights, revenue attribution.
Common ATS mistakes:
  - Saying “built dashboards” without naming the business KPI or decision supported.
  - Missing core keywords from JDs (dbt, Snowflake, BigQuery, semantic layer, governance).
  - Only listing tools without showing what you modeled or automated.
  - No mention of data quality, definitions, or reliability.
  - Bullets lack measurable impact (time saved, adoption, accuracy, revenue insights).
Core Skills: SQL, Dimensional Modeling, ETL/ELT, Metrics Definitions, Data Quality, Dashboard Design, Cohort Analysis
Tools/Tech: SQL, dbt, Snowflake, BigQuery, Tableau, Power BI, Looker, Airflow, Fivetran
Metrics & Verbs: MRR, ARR, ARPU, Churn, Retention, Funnel Conversion, Forecasting, Modeled, Instrumented, Automated, Standardized, Visualized

Examples

Built a single-source-of-truth revenue model (dbt + Snowflake) and reduced reporting disputes by 60%.
Automated weekly exec dashboard refresh and cut reporting time from 6 hours to 45 minutes.
Created churn cohort views that improved early risk detection and reduced at-risk accounts 12%.

Check my resume for missing keywords Generate keywords from a job description