Data Analyst CV Template and Example

Professional

A strong Data Analyst CV shows the tools you use, the data you worked with and the decisions your analysis changed. Hiring managers look for SQL and a visualisation tool first, then evidence that your work had a measurable effect on a team or a number. This page gives you a complete example CV and notes on how to write each section.

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Data Analyst CV example (Professional template)

A full-page example built for this role. Use it as a structure reference — replace every line with your own experience.

Skills hiring managers look for in a Data Analyst

SQL (joins, window functions, CTEs)
Python or R for analysis
Power BI, Tableau or Looker
Excel and Google Sheets
Data cleaning and validation
Dashboard design
A/B test and experiment analysis
Cohort and retention analysis
Forecasting
Stakeholder communication
dbt or similar transformation tools
Statistics fundamentals

What to include in a Data Analyst CV

A Data Analyst CV needs five things: a short summary, a skills list, your work experience, your education and any certifications. Projects and a portfolio link are optional but useful if you are early in your career or moving in from another field.

Keep it to one or two pages. Recruiters screening analyst roles typically scan for the tools first, so put SQL, your main visualisation tool and your analysis language near the top. Everything below that should support those claims with specifics.

Contact details and a portfolio or GitHub link if you have public work
A three-sentence summary naming your tools and the type of data you have worked with
A skills list of 10 to 14 items, grouped by category if it helps readability
Work experience in reverse chronological order with quantified results
Education, plus certifications that are relevant to the tools you list

How to write experience bullets for analyst roles

The most common weakness in analyst CVs is describing tasks instead of outcomes. 'Responsible for reporting' tells a hiring manager nothing. 'Built a Power BI dashboard that replaced 14 manual reports and cut the weekly reporting cycle from six hours to 40 minutes' tells them what you can do and what it was worth.

Each bullet should follow a simple pattern: what you did, with which tool or method, and what changed as a result. The result does not have to be revenue. Time saved, error rates reduced, requests eliminated and decisions supported are all valid outcomes.

Name the tool or method in the bullet, not just in the skills list
Give a number wherever you honestly can: hours saved, percentage change, number of records, number of users
Describe the audience when it matters, for example 'reported to the finance team' or 'used by 30 store managers'
Avoid vague verbs like 'helped with' or 'assisted on' — start with what you built, analysed or delivered

Skills hiring managers scan for

Most analyst job ads ask for the same core set: SQL, one visualisation tool, one scripting language and spreadsheet skills. If you have all four, list them clearly and early. If you are missing one, do not pad the list with unrelated tools to compensate — it is obvious and it weakens the rest of the CV.

Beyond tools, list analytical methods you can genuinely discuss in an interview. A/B testing, cohort analysis, forecasting and data validation are common requirements and are worth naming explicitly. Only include methods you could explain with an example from your own work.

SQL: state the dialect or platform you know, such as PostgreSQL, BigQuery or Snowflake
Visualisation: Power BI, Tableau or Looker, and mention DAX or calculated fields if relevant
Programming: Python with pandas, or R with tidyverse
Methods: experiment analysis, retention and cohort work, forecasting, data quality checks
Soft skills: only include these if the CV is short — one line on stakeholder communication is enough

Certifications and projects that help

Certifications carry the most weight when you are changing careers or have less than two years of experience. The Google Data Analytics Certificate and the Microsoft PL-300 for Power BI are both widely recognised. If you already have three or more years of analyst experience, your work history matters more than certificates, and you can list them in a single compact section.

A small portfolio project can be worth more than a certificate because it shows your process. A dashboard with a documented data source, cleaning steps and a short written summary demonstrates the same skills an employer would test in a technical interview.

List certifications with the full name and the issuing body
For projects, state the dataset size, the tools used and what you concluded
Link to a public dashboard or repository if one exists
Do not list courses you did not finish or certificates you have not yet passed

Common mistakes in Data Analyst CVs

The most frequent problem is a skills list that does not match the experience section. If Python is in your skills but never appears in a bullet, a reviewer will assume you have used it once. Either add a bullet that shows it in use or move it to a lower-priority line.

The second most common issue is unquantified work. Analysts are hired to produce evidence, so a CV with no numbers in it reads as a mismatch. Even approximate figures are better than none, as long as you can explain them in an interview.

Finally, avoid listing every tool you have ever touched. A focused list of eight to twelve skills that you can defend in detail is stronger than twenty that invite questions you cannot answer.

Skills that never appear in the experience section
Bullets with no measurable result
Generic summaries that could describe any analyst in any industry
Long lists of tools with no depth behind them
Typos in tool names, which are noticed more often than you would expect

Data Analyst CV — frequently asked questions

How long should a Data Analyst CV be?

One page is enough if you have under five years of experience, and two pages is normal beyond that. Length matters less than density: every line should carry a tool, a method or a result. If a bullet does not do any of those three things, cut it.

Do I need a portfolio to get a Data Analyst job?

It is not required, but it helps, particularly for career changers and recent graduates. Two or three well-documented projects are more useful than ten unfinished ones. A public dashboard with a clear data source and a short written summary is the most effective format.

Which certifications are worth listing on a Data Analyst CV?

The Google Data Analytics Certificate and the Microsoft PL-300 for Power BI are the most widely recognised entry-level options. If you already have several years of experience, certifications matter less than your work history, so keep them to a short section at the bottom.

How do I write about analysis work if I do not have exact numbers?

Use honest approximations and be ready to explain how you arrived at them. 'Reduced a recurring report from roughly six hours to under one hour' is fine if that reflects what happened. Never invent figures you cannot defend, because interviewers will ask.

Should I tailor my Data Analyst CV for every application?

Yes, at least at the skills and summary level. Read the job ad, note which tools and methods it names, and make sure the ones you genuinely have appear in your summary and skills list. Reordering your skills to match the ad takes a few minutes and makes a measurable difference to screening.