Data Analyst Resume Keywords (Tools and Platforms Keywords + ATS Examples)
Analyst roles often specify exact BI and warehouse tools. Literal alignment with the posting improves ATS match quality.
BI & visualization platforms
Primary analyst surfaces.
- Tableau
- Looker
- Power BI
- Mode
- Sigma
- Metabase
- Qlik
- Google Data Studio
- ThoughtSpot
- Hex
Weak: Looker
Strong: LookML refinements for certified revenue metrics.
Weak: Power BI
Strong: Row-level security for regional sales views.
Warehouses & query engines
Where data is queried.
- Snowflake
- BigQuery
- Redshift
- Databricks SQL
- Presto
- Trino
- Athena
- Synapse
- Postgres
- Vertica
Weak: Snowflake
Strong: Warehouse tuning for large joins on marketing events.
Weak: BigQuery
Strong: Partitioning and clustering to reduce scan costs.
Transformation & orchestration
Analytics engineering overlap.
- dbt
- Airflow
- Fivetran
- Stitch
- Airbyte
- Matillion
- Prefect
- Dagster
- cron
- data tests
Weak: dbt
Strong: Tests on grain and uniqueness preventing bad dashboard numbers.
Weak: Fivetran
Strong: Connector issues triaged with vendor and engineering.
Collaboration & ticketing
How work flows.
- Jira
- Linear
- Asana
- Confluence
- Notion
- Slack
- ServiceNow
- Zendesk
- Google Sheets
- Excel
Weak: Jira
Strong: Analytics requests triaged with definition of done and metric owners.
Weak: Confluence
Strong: Metric dictionary maintained for cross-team alignment.
Experimentation & product analytics tools
Growth-oriented analysts.
- Amplitude
- Mixpanel
- Heap
- Optimizely
- Statsig
- Google Analytics 4
- Adobe Analytics
- Segment
- mParticle
- Singular
Weak: Amplitude
Strong: Cohort charts feeding weekly growth experiment reviews.
Weak: Segment
Strong: Tracking plan governance reducing schema drift.
Where to use these keywords (ATS + readability)
Skills
Put the BI + warehouse combo from the JD first.
Experience bullets
Show dashboards you owned, not ‘exposure’ to a tool.
Skills
Include dbt/Airflow when job is analytics-engineering-heavy.
Summary
Name primary business domain (marketing, finance, product).
Experience bullets
Reference ticketing when stakeholder intake is part of the job.
Common mistakes
- Listing every BI tool—credibility drops.
- Warehouse named without SQL depth in bullets.
- No experimentation tools for growth roles.
- Ignoring collaboration stack when remote/async-heavy.