CV Template
Data Analyst CV Template & Examples (ATS-Optimized)
Data Analyst hiring rewards people who turn raw data into decisions, blending SQL fluency, clean visualization, and sharp business storytelling. Recruiters and ATS engines scan for query skills, BI tools like Tableau or Power BI, and evidence your analysis changed an outcome. This template positions your dashboards and findings so the parser indexes every keyword and the hiring manager sees the value you delivered.
Written & reviewed by the CVWon Editorial Team · Updated June 2026
Build Your CV NowTo write a strong Data Analyst CV, lead with Technical Skills, Professional Experience and Analytics Projects — each backed by specific, quantified results rather than generic duties. A strong Data Analyst CV shows you answer business questions, not just build charts, by pairing each analysis with the decision it informed.
ATS Optimisation
ATS Keywords
Include these keywords in your CV to pass applicant tracking systems.
A strong Data Analyst CV shows you answer business questions, not just build charts, by pairing each analysis with the decision it informed. The best candidates quantify outcomes such as a dashboard that cut reporting time 70% or a cohort analysis that reshaped retention strategy and lifted renewals 11%. Recruiters look for SQL depth, comfort across BI tools, and the ability to translate numbers into plain-language recommendations for non-technical stakeholders. Weak CVs list 'proficient in Excel and Tableau' without a single result attached. Strong ones name the data sources, the method, and the action taken. The clearest differentiator is evidence that leadership acted on your insights and the business changed because of them.
Structure
What Sections Should a Data Analyst CV Include?
Technical Skills
ATS matches the exact query languages and BI tools listed in the posting.
Example
SQL, Python (pandas), Tableau, Power BI, Excel (advanced), BigQuery, DAX, Google Analytics
Professional Experience
Recruiters want analyses that drove decisions, not a catalogue of recurring reports.
Example
Built an executive churn dashboard in Power BI that cut weekly reporting time 70% and flagged at-risk accounts.
Analytics Projects
Shows initiative and end-to-end analysis beyond assigned recurring tasks.
Example
Ran a cohort retention analysis in SQL revealing a 22% week-4 drop-off, informing a fix that lifted renewals 11%.
Business Impact Highlights
Proves your insights changed strategy, which separates analysts from report-runners.
Example
Identified $340k in annual savings by analysing supplier spend patterns across 18 months of invoices.
Education & Certifications
Validates analytical foundations and tool proficiency for self-taught candidates.
Example
BSc Economics; Google Data Analytics Professional Certificate; Microsoft Power BI Data Analyst (PL-300).
Avoid These
What Are Common Data Analyst CV Mistakes?
FAQ
Frequently Asked Questions
One page for most candidates, two only with extensive senior experience. Lead with three or four analyses that drove decisions, each with a quantified outcome, rather than listing every report you ever produced.
A Data Analyst CV emphasises SQL, BI dashboards, and translating data into business decisions, while a Data Scientist CV centres on machine learning, statistical modelling, and production deployment. Pitch to the role you want; do not blur the two.
The Google Data Analytics Professional Certificate and Microsoft PL-300 (Power BI Data Analyst) are widely recognised. They reassure recruiters of tool fluency and help self-taught or career-switching candidates pass initial screens.
Not always; many roles run primarily on SQL and a BI tool. Python is a strong differentiator for data cleaning and automation, so list it if you have it, but rock-solid SQL is the non-negotiable foundation.
Use percentages and relative figures instead of absolute revenue, such as 'reduced reporting time 70%' or 'lifted renewals 11%'. This demonstrates measurable value while respecting any confidentiality constraints from past employers.
Salary
Salary by Experience Level
Typical salary ranges by seniority (EUR, gross).
| Level | Experience | Salary range |
|---|---|---|
| Entry Level | 0–2 years | €35K – €55K |
| Mid Level | 3–5 years | €55K – €85K |
| Senior Level | 6–10 years | €85K – €130K |
| Lead / Manager | 10+ years | €120K – €170K |
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