Data
Data Analyst CV: what employers ask for
Data analyst roles are about turning data into decisions. Screeners look for the questions you answered, the tools you used to answer them and what the business did next. A CV that lists SQL and Tableau without a single decision it influenced is easy to pass over.
From real postings
We read 34 Data Analyst job postings from 20 companies on 6 November 2026. The most named asks were SQL (27), Stakeholder management (25) and Metrics / KPIs (22). 21 postings stated years of experience; the middle value was 3.
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What a strong Data Analyst CV looks like
Start here if you are editing a CV today. The evidence for each point follows below.
Section order, top to bottom
- HeaderName, email, phone, city, and a link to one analysis you can show, if you have one.
- SummaryTwo or three lines: your title, years of experience, your tools, and the kind of decisions your work supports.
- ExperienceMost recent first. Bullets about questions answered and decisions changed, with the tool named inside.
- SkillsGrouped: SQL, Python or R, BI tools (Tableau, Looker, Power BI), statistics.
- ProjectsUseful when moving into analysis: one real dataset, a clear question, and what you found.
- EducationDegree and any relevant courses, kept short once you have work experience.
The summary
Say who uses your work and for what. Working with stakeholders was named almost as often as SQL in our sample.
Data analyst with three years of experience in SQL, Python and Tableau. I build the reporting our sales and finance teams plan with, and answer the questions behind the numbers.
Skills: show them, do not just list them
SQL was the most named skill, followed by stakeholder work, metrics and Python. Show SQL and Python through analyses that changed something, and name the people who acted on them.
Weak and strong bullets
Illustrative rewrites, not real candidates. Use your own work, and only numbers you can back up.
Weak: Created dashboards in Tableau.
Stronger: Built the weekly sales dashboard in Tableau used by 25 regional managers, replacing a manual Excel report that took a day to prepare.
Why it works: Names the tool, the audience and the time it saved.
Weak: Analysed customer data.
Stronger: Found in churn analysis that customers without onboarding calls left at twice the rate, which led the team to make the call standard.
Why it works: An insight with a decision attached. That is the core of an analyst CV.
Weak: Ran A/B test analysis.
Stronger: Analysed 14 pricing-page experiments and flagged two early calls that were not statistically significant, avoiding a misleading rollout.
Why it works: Shows statistical judgement, not only tool use.
What Data Analyst job postings ask for
Counted from 34 real postings, not guessed. When you paste a posting into Resymetry, it checks each of these asks against your CV and marks it as shown, only listed, or missing.
| Skill or ask | Postings naming it | Only as nice to have |
|---|---|---|
| SQL | 27 of 34 | 2 |
| Stakeholder management | 25 of 34 | – |
| Metrics / KPIs | 22 of 34 | 1 |
| Python | 20 of 34 | 3 |
| Cross-functional work | 17 of 34 | – |
| Prioritisation | 16 of 34 | – |
| Statistics | 14 of 34 | – |
| Tableau | 13 of 34 | 3 |
| Data quality / governance | 12 of 34 | 1 |
| Data modelling | 11 of 34 | – |
Show 8 more
| Skill or ask | Postings naming it | Only as nice to have |
|---|---|---|
| dbt | 11 of 34 | 3 |
| BigQuery | 10 of 34 | 3 |
| LLMs / generative AI | 9 of 34 | 3 |
| Looker | 9 of 34 | – |
| Data pipelines | 8 of 34 | – |
| A/B testing / experimentation | 7 of 34 | – |
| B2B / SaaS | 7 of 34 | 3 |
| Budget | 7 of 34 | – |
This is a small sample, so read it as a direction rather than a measurement. Product, marketing, BI and insights analyst titles are included.
How we counted
On 6 November 2026 we read 34 live Data Analyst postings from 20 companies, through their public job boards (Greenhouse, Lever and Ashby). A posting counted when its title matched the role. We took at most three per company, so no single employer sets the result.
A skill counts once per posting, when it is named outside the benefits and company boilerplate. Matching is by keyword, so read the numbers as “named in”, not “strictly required”. “Only as nice to have” means it appeared only under a heading such as “Nice to have” or “Bonus”. 22 of the 34 postings had such a heading, so that column is a floor.
By location on the posting: 12 US, 2 UK, 9 India, 11 elsewhere or remote. Most employers in the sample are technology companies, which skews the result towards their stacks.
Companies sampled: Anduril, Brex, Cloudflare, Fivetran, Flexport, GitLab, GoCardless, Graphcore, HackerRank, MongoDB, Mozilla, Okta, Paytm, Riot Games, Roblox, Scale AI, Stripe, Supabase, Toptal, Vanta.
The script that produced these numbers is scripts/role-postings.mjs in the Resymetry repository. It stores counts only, never the text of a posting.
What employers look for in a Data Analyst CV
Screeners check these first. Each one should be visible in your job entries, not only in a skills list.
- Confident SQL, shown through the analysis it enabled.
- A visualisation or BI tool named in the posting, such as Tableau, Power BI or Looker.
- Analyses that led to a decision or change, with the result where you know it.
- Working with stakeholders: turning vague questions into clear analysis and explaining results simply.
- Basic statistics where relevant, such as A/B test analysis or forecasting.
4 common Data Analyst CV mistakes and how to fix them
Bullets about building dashboards with no mention of who used them.
Fix: Say who relied on the dashboard and what it helped them decide.
No business outcomes.
Fix: Name at least one decision your analysis changed, and its effect if you know it.
Listing Python or statistics you have only studied.
Fix: Keep study-only skills in an education or learning line, not in job achievements.
Jargon that hides the point.
Fix: Write for a hiring manager who is not an analyst: question, method, result.
Starting from scratch, or the layout is the problem rather than the content? There are free ATS CV templates to start from.
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Data Analyst CV questions
- What skills should a data analyst CV highlight?
- SQL, one BI tool from the posting, spreadsheet skills and clear communication. Show each through an analysis you actually did.
- Do data analysts need Python?
- Many postings list Python or R as a plus rather than a requirement. Include it if you have used it at work, and say what for.
- How do I show impact as a junior data analyst?
- Describe the question, what you found and who used it. A clear decision you informed counts, even without a revenue figure.