Data analyst resume template
See the finished document, where its evidence is, and the plain text a parser pulls out. Then put your own story in it.
- Review score
- 97
- Evidence
- 100%
- Words
- 264
Scored by the same rules the Studio uses. How scoring works
Analyst with five years turning warehouse data into revenue decisions at marketplace and fintech companies. Modelled 180M rows in SQL and dbt, cut reporting turnaround 70%, and drove pricing changes worth $2.4M.
- Own the pricing analytics model end-to-end, informing $2.4M in annual margin decisions with 4 stakeholder teams each quarter.
- Design dbt models over 180M order rows against a 6am freshness SLA, cutting the finance close from 9 days to 2.
- Automate 23 recurring Looker reports, returning 31 hours per week to a 6-person analytics team.
- Built a churn model in Python flagging 12K at-risk accounts per month, driving a retention campaign worth $780K.
- Replaced 40 hand-maintained spreadsheets with a governed Snowflake layer, removing 6 recurring reconciliation errors.
- Developed 60 Tableau dashboards used weekly by 240 staff across 3 business units.
- Reduced warehouse query cost 44% by refactoring 18 nightly jobs, scaling to 3x data volume with no added spend.
Opens in the Studio on this device, in the Executive layout. Replace the sample details with your own before you export.
Try it with your name
A preview only. Nothing is saved.
Analyst resumes fail for a specific reason: they describe tools instead of decisions. Listing SQL, Tableau and Python tells a hiring manager what you touched, not what changed because you touched it. The template above is written the other way round, and the score on this page is the actual output of the Review, not a marketing number.
Data analyst resume summary example
- SQL
- dbt
The candidate is fictional, so swap in your own numbers. Stuck? The resume summary generator drafts one from your title and results.
Why most data analysts don't get the call
The decision, not the dashboard
"Built 40 dashboards" is a workload. "Built the pricing model behind $2.4M of margin decisions" is an outcome. Analysts get filtered out at the first skim because their bullets end at the artefact. Push every bullet one step further: who acted on it, and what moved.
Row counts and refresh cadence are your scale numbers
Engineers have latency and QPS. Analysts have rows modelled, tables owned, reports served, and how fast the data lands. "180M order rows" and "a 6am freshness SLA" tell a reviewer what size of environment you can survive in.
SQL depth gets probed within ten minutes
Window functions, CTEs, incremental models and query cost show up in nearly every analyst screen. If you have tuned a warehouse bill or rewritten a nightly job, that belongs on the page — it separates you from someone who only ever wrote SELECT statements in a BI tool.
Say which methods, not "statistical analysis"
Keyword filters match literal terms. A/B testing, cohort analysis, regression, forecasting and attribution are searchable. "Strong analytical skills" matches nothing and signals nothing.
Skills and keywords for a data analyst resume
Applicant tracking systems match on literal strings. Spell each term the way the job posting spells it, and group related skills so people and parsers can both follow it.
Query & languages
- SQL
- Python
- R
- DAX
- pandas
- NumPy
BI & modelling
- dbt
- Tableau
- Looker
- Power BI
- Mode
- data modelling
- star schema
- semantic layer
Platforms
- Snowflake
- BigQuery
- Redshift
- Databricks
- Airflow
- Fivetran
- ETL
- data warehouse
Methods
- A/B testing
- experimentation
- cohort analysis
- regression
- forecasting
- attribution
- segmentation
- KPI reporting
Have the real job posting? Paste it into the keyword scanner to see the skills it asks for most, and which ones your resume is missing.
Why each choice was made
Why the skills section is split four ways
A single block of twenty tools reads as noise and trips the engine's ungrouped-skills rule. Four labelled groups let a keyword filter match the string and a human skim the shape of your stack in about two seconds.
Why dollar figures appear next to technical work
Analyst work is easy to describe as internal plumbing. Attaching the business number — $780K retention campaign, $1.1M reallocated spend — is what moves a bullet from support function to revenue function in a reviewer's head.
Where to put a portfolio
One link in the header, next to LinkedIn. A GitHub with three real notebooks beats a Projects section that repeats what your job already proves.
Data analyst resume questions
What skills should I put on a data analyst resume?
The skills the job posting names, spelled the way it spells them. For a data analyst that often includes SQL, Python, dbt, Tableau, Snowflake and BigQuery. Show each one in a bullet with a result, then list the core ones again in a short skills section.
How do I write a data analyst resume summary?
Keep it to two or three sentences: your years of experience and where, the scale of your work, and one result with a number. Leave out words a recruiter cannot check, like hardworking or passionate. The example summary on this page shows the pattern.
Is this data analyst resume template free?
Yes. Open it in the Studio, replace the example with your own work and download it as a PDF or Word file. There is no watermark; downloading needs a free Google sign-in.
Is this data analyst resume template ATS friendly?
Yes. It is one column of real text with standard section headings, and no tables, text boxes or text inside images, so parsers read it in order. Run your finished file through the free ATS resume checker to see the text it gives back.
Keep the pattern. Tell your story.
The Studio opens with this data analyst example loaded. Edit any bullet and the Review score updates as you type. Editing needs no account; sign in with Google, free, to download.
- Keep the hierarchy. Same section order, plain-text contact details.
- Replace every claim. Your scope, your numbers, your tools. Never borrowed achievements.
- Run the Review again. Watch the score respond to the evidence in your version.
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Other role examples scored the same way
What each system will do to this file.
What each applicant tracking system accepts, read from the vendor's own documentation.
- GreenhouseAccepts PDF, DOC, DOCX, RTF, TXT · parses up to 2.5 MB.
- Oracle TaleoAccepts PDF, DOC, DOCX, RTF, TXT, HTML, ODT, WPD · up to 5 MB · Varies by employer engine.
- SmartRecruitersAccepts PDF, DOC, DOCX, RTF, JPG, PNG · up to 2 MB · Textkernel engine.
- AshbyAccepts PDF, DOC, DOCX · up to 50 MB.
- WorkableAccepts PDF, DOC, DOCX, RTF, HTML, ODT · up to 5 MB.
- ManatalAccepts PDF, DOC, DOCX, RTF · Manatal (in-house) engine.