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Resume TipsOctober 5, 2025· 7 min read

Data Analyst Resume: Keywords and Format That Pass ATS in 2026

Data roles are among the most keyword-sensitive for ATS. Here's exactly what to include — from SQL to storytelling — to get your analyst resume past the filter.

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Data analyst roles attract candidates from statistics, computer science, economics, and finance. The skills overlap considerably between candidates — which means ATS keyword matching and clear formatting become the primary differentiators at the screening stage.

Here's what to include and how to structure your resume to pass ATS and make a compelling case to the hiring manager who reads it next.

The Keywords That Matter Most for Data Analysts

Technical skills — exact match required:

  • SQL (and specific dialects: PostgreSQL, MySQL, BigQuery, Snowflake)
  • Python (pandas, NumPy, scikit-learn, matplotlib)
  • R (if relevant to your background)
  • Excel and Google Sheets (still widely required, especially in non-tech industries)
  • Visualisation tools: Tableau, Power BI, Looker, Metabase
  • Data pipelines and ETL: dbt, Airflow, Fivetran, Stitch
  • Cloud platforms: AWS, GCP, Azure (and specific services: Redshift, BigQuery, Azure Synapse)
  • A/B testing and statistical analysis

Domain and process terms:

  • Data analysis, data modelling, data visualisation
  • KPI, metrics, dashboard, reporting
  • Business intelligence, analytics engineering
  • Stakeholder communication, data storytelling
  • Hypothesis testing, regression analysis, cohort analysis

How to Write Data Analyst Bullet Points

Every bullet should demonstrate three things: what you analysed, what tool or method you used, and what decision or outcome resulted.

Weak: "Created dashboards for the marketing team."

Strong: "Built a Tableau dashboard tracking 12 marketing KPIs across 4 channels, enabling the team to reallocate £120K in quarterly spend based on ROAS data — improving overall campaign ROI by 28%."

The strong version includes: Tableau, marketing KPIs, specific decision, and a business outcome. All searchable. All credible.

The Skills Section

Your skills section should be comprehensive and grouped by category for readability:

  • Languages: Python, SQL, R
  • Tools: Tableau, Power BI, dbt, Airflow
  • Databases: PostgreSQL, BigQuery, Snowflake
  • Methods: A/B testing, cohort analysis, regression modelling

Format for Data Analyst Resumes

Single column. Standard section headers. Clean PDF export. The visual polish common in data portfolios (interactive notebooks, infographic CVs) does not belong on your application resume — ATS can't read it and recruiters find it distracting.

Tailor for the Industry

Data analyst roles vary enormously by industry. A fintech analyst role looks for different context than a healthcare analytics role. Read the job description carefully — the industry-specific terminology (credit risk, patient outcomes, ad attribution) should appear in your resume where it's genuinely relevant to your experience.

Portfolio Link

Include a link to your GitHub, Kaggle profile, or personal site alongside your contact information. A portfolio doesn't replace keywords — but it reinforces them for the human who reads your resume after it passes ATS.

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