Data Analyst Resume Example and Guide
A complete sample, plus what to write when your job was mostly dashboards and reports.
For analysts with 0–5 years, and anyone moving into analytics from a reporting or support role.
A data analyst resume has one job: show that your work changed a decision. Most analyst resumes list tools instead — SQL, Excel, Power BI — which every other applicant also lists. The ones that get interviews name the question they answered, the size of the data, and what the business did differently afterwards.
What recruiters look for first
- SQL first. It appears in almost every analyst job description and is the one skill that gets filtered on.
- Evidence you worked with real, messy data — row counts, number of sources, how often it refreshed.
- A decision or a saving that followed your analysis, not just the chart you built.
- One visualisation tool you actually know well, rather than five you've touched.
- Business context: which team used your work, and for what.
Summary examples
Statistics graduate who has built end-to-end analyses in SQL and Python, including a 2M-row retail project that identified ₹4 lakh of annual stock write-off. Comfortable owning a question from data pull to the slide that explains it.
Data analyst with 3 years in retail and e-commerce, working with SQL, Python and Power BI. Built the reporting that the sales leadership now runs its weekly review on, and cut the time to produce it from two days to twenty minutes.
Bullet points, before and after
Responsible for creating dashboards in Power BI
Built 12 Power BI dashboards used weekly by 40 people across sales and supply chain, replacing a manual Excel pack
Names the audience and what it replaced, so the reader understands the scale and the before-state.
Worked on data cleaning and SQL queries
Rewrote 30 reporting queries and added incremental loads, cutting the nightly refresh from 90 to 11 minutes
A specific technique with a measured result, rather than the name of a tool.
Helped the marketing team with campaign analysis
Analysed 18 months of campaign data to show that two channels drove 70% of signups, which moved ₹12 lakh of spend
Ends on the decision the analysis caused — the part that proves impact.
Made reports for management
Replaced a weekly status email with a self-serve report, removing a recurring 6-hour task from the team's week
Time saved is a number you almost always have, even when revenue figures are confidential.
Keywords to include
Terms that job descriptions for this role use, and that applicant tracking systems are often configured to match. Include the ones that are genuinely true of you.
Core
- SQL
- Excel
- Python
- Data analysis
- Data visualisation
- Reporting
- ETL
Tools
- Power BI
- Tableau
- Looker
- Google Analytics
- BigQuery
- Pandas
- NumPy
Methods
- A/B testing
- Cohort analysis
- Forecasting
- Dashboard design
- Data modelling
- Stakeholder management
Mistakes specific to this role
A wall of tools with no context
A skills section listing twelve tools tells a recruiter nothing about depth. Keep the list, but make sure the experience bullets show two or three of them being used on a real problem.
Describing the dashboard instead of the decision
"Built a sales dashboard" is a task. "Built the dashboard the sales review now runs on" is a result. The second tells the reader your work was adopted.
Hiding the data size
Working with 2 million rows across four systems is a different job from working with a 500-row spreadsheet. Say which one it was.
No numbers because the real ones are confidential
You can almost always give percentages, time saved, number of users, or the count of reports and sources — none of which reveal commercially sensitive figures.