Resume example · For job seekers
Data Analyst Resume Example
A full data analyst resume example, with summaries for each level, the skills to list, bullets that show impact, and how to get past applicant tracking.
The short answer
A strong Data Analyst resume opens with a short summary, groups the skills employers will test, and backs each role with bullets that show what changed because of your work. Below is a full example, summary wording for entry level or graduate, career changer, mid level and senior candidates, and how to get through applicant tracking systems.
- Keep it to one page if you have under about five years of experience; two is fine beyond that if every line earns its place.
- Use a single-column layout with standard headings, so both people and parsing software read it in the right order.
- Lead each bullet with a verb and end it with the outcome: what was faster, cheaper, clearer or decided because of your work.
A data analyst resume is judged the way analysts judge data: does it answer the question quickly, and can the claims be checked? Hiring managers want to see which tools you use, what kind of questions you have answered with them, and what changed because of your work. This guide walks through each part of the resume, with a full example you can adapt, wording for every career stage, and the mistakes that send otherwise capable analysts to the bottom of the pile.
Example Data Analyst resume
Jordan Ellis
Data Analyst
Manchester, UKjordan.ellis@example.comexample.com/jordan-portfolio
Summary
Data analyst with four years in retail and logistics, working mainly in SQL, Power BI and Python. Builds the reporting teams run their week on and the analyses that settle a decision, and documents metric definitions so the numbers stay consistent.
Skills
- Languages
- SQL, Python (pandas), DAX
- Tools
- Power BI, Excel, dbt, Git, Snowflake
- Methods
- Data cleaning and validation, A/B test analysis, Data modelling
Experience
Data Analyst · Northwind Traders, Manchester
2023 – present
- Rebuilt the weekly trading dashboard in Power BI as a single model, replacing five spreadsheets and the manual Monday pack.
- Wrote the definitions for the business’s core sales metrics and had them agreed by finance and marketing.
- Analysed delivery performance by depot and carrier; operations used the findings to rebalance routes in two regions.
- Moved recurring SQL into tested dbt models, so changes are reviewed in Git before they reach reports.
Junior Data Analyst · Contoso Logistics, Leeds
2021 – 2023
- Automated the monthly stock report with SQL and a scheduled refresh, freeing analyst time for ad hoc requests.
- Built morning data-quality checks that flagged missing and duplicate orders before they reached reports.
- Answered weekly questions from the operations team, from carrier costs to returns by product line.
Education
BSc Economics · Contoso University
2018 – 2021
Dissertation on regional house prices using public data in R.
Projects
- Bus punctuality analysis: public timetable and arrival data, cleaned in Python and presented in a Power BI report with the code on GitHub.
Summary examples
Three or four lines at the top of the page. Pick the one closest to your situation and rewrite it with your own tools and work.
Entry level or graduate
Career changer
Mid level
Senior
Skills to list
Hard skills
Soft skills
List only what you could be tested on. Soft skills carry more weight shown in a bullet than named in a list.
Check the skills on your Data Analyst resume
Run an AI job simulation of Data Analyst work and get a scored report on which of the skills you list are strongest, and which to work on before you apply. 3 free tests, no card.
Experience bullet points
Reporting and dashboards
- Rebuilt the weekly trading dashboard in Power BI from five spreadsheets into one model, so regional managers saw the same figures on Monday morning without waiting for a manual pack.
- Wrote and documented the definitions behind twelve core metrics, ending recurring disputes between finance and marketing over which revenue number was right.
- Automated a monthly stock report with SQL and a scheduled refresh, freeing a day of analyst time each month for ad hoc questions.
Analysis that changed a decision
- Analysed delivery times by postcode and carrier, showing that late deliveries were concentrated in two depots; operations used the findings to rebalance routes.
- Compared customer retention across sign-up channels and found that one paid channel brought customers who rarely made a second order, which led marketing to cut its budget.
- Designed the measurement plan for a pricing test, agreeing the success metric and sample size with the product team before launch.
Data quality and tooling
- Built validation checks that flag missing or duplicate orders in the warehouse each morning, catching load failures before they reached reports.
- Moved the team’s recurring queries into dbt models with tests, so changes were reviewed in Git rather than edited in place.
What to include
Header
Name, location (city and country is enough), email, and a link to your portfolio, GitHub or LinkedIn. Leave out your full address, date of birth and photo unless the country you are applying in expects them.
Professional summary
Three or four lines: your level, the tools you use most, the kind of problems you solve and the kind of role you want. Tailor the tools to the job advert.
Skills
Group them (languages, BI tools, methods) rather than listing twenty words in a row. Only list what you could be tested on tomorrow.
Experience
Reverse chronological. Three to five bullets per role, each naming the task, the tool and what changed. Non-analyst jobs still count if you worked with data in them.
Projects
Essential for entry-level candidates and career changers. Name the dataset, the question, the tools and the finding, and link to the work.
Education and certifications
Degree, institution and dates. Add relevant certificates (such as a vendor BI certification) if they back up a skill your experience does not yet show.
Formatting
- Keep it to one page if you have under about five years of experience; two is fine beyond that if every line earns its place.
- Use a single-column layout with standard headings, so both people and parsing software read it in the right order.
- Lead each bullet with a verb and end it with the outcome: what was faster, cheaper, clearer or decided because of your work.
- Use real figures from your own work where you can explain them in an interview; leave a number out rather than guess one.
- Save as PDF unless the application asks for a Word document, and name the file with your name and the role.
Getting past applicant tracking systems
- 1Mirror the exact tool names in the advert: if it says Power BI and Looker, write both if you use both, not just “BI tools”.
- 2Keep skills in plain text, not inside images, icons or skill-level bars that software cannot read.
- 3Use standard section headings such as Experience, Education and Skills.
- 4Avoid tables and text boxes for the main content; some systems read them out of order or skip them.
- 5Spell out abbreviations once where they might be searched either way, for example “extract, transform, load (ETL)”.
Common mistakes
- Listing tools without showing what you did with them.
- Describing duties (“responsible for reporting”) instead of results.
- Claiming advanced skills, such as machine learning, that the rest of the resume does not support.
- Including a portfolio link that is broken, private or full of unfinished notebooks.
- Sending the same resume to every advert instead of matching the tools and language of each one.
Common questions
Should a data analyst resume be one page?
One page is the safe default for anyone with under about five years of experience. A second page is fine for senior analysts when it holds relevant work, not when it repeats the same duties for older roles.
Do I need a portfolio as well as a resume?
It is not always required, but it helps most when your job history does not show analysis yet. One or two finished projects with a clear question and a readable write-up do more than many half-finished notebooks.
Is a CV the same as a resume?
In the UK, a CV usually means the same short document that people in the US call a resume. In academic and some international applications a CV is longer and lists publications and research. Use whichever word the advert uses.
Which skills should I put first?
The ones named in the advert that you can demonstrate. For most analyst roles that means SQL, a spreadsheet tool and the BI tool the team uses, followed by Python or R if the role asks for it.
Know which skills on your resume you can back up
Cohesyve runs an AI job simulation of the Data Analyst role and gives you a scored report, so you go into the employer's own assessment knowing where you stand.
3
free tests
$0
no card required
Full
report on your first 3
Any
real job posting
3 free tests · No card required · Pro $20/mo
Hiring a Data Analyst rather than applying? Cohesyve finds and contacts candidates from your job description, tests them on a simulation of the real work and ranks them.
From the blog