Entry-level data analyst resume example

What recruiters look for

• SQL you have used on real data: name the database and say what the query did (reconciled, joined, found). SQL is the first screen for almost every analyst role.
• One BI tool used for real people: Power BI, Tableau or Looker, with who used the report and how often.
• Care with accuracy: catching errors, reconciling sources and documenting definitions. A wrong number costs an analyst more trust than a slow one.
• Communication: analysts who explain caveats in plain words get promoted. Show requests handled and audiences presented to.
• A project on messy public data: if your work history is thin, it is the best evidence you can do the job.

Writing the summary

Two or three sentences: what you have worked on (industry and data), your core tools, and one habit that makes you trustworthy. Skip “detail-oriented team player”; show it in the bullets instead.

Bullet points that work

Strong lines for this role, beyond the ones in the example. Borrow the shape and put in your own numbers.

• Rebuilt a monthly sales workbook as a Power BI report with scheduled refresh, removing 2 days of manual copying each month.
• Wrote a data dictionary for 45 fields in the customer table, ending recurring disputes over what “active customer” means.
• Found a timezone error that shifted 8% of orders into the wrong day, and fixed it in the source query.
• Cleaned and merged 3 years of survey responses (14,000 rows) for a program evaluation report shared with the board.
• Built an Excel model of shipping costs by zone that the logistics lead used to renegotiate 2 carrier contracts.
• Answered 200+ data requests in a year with a median turnaround of 2 business days.
• Presented findings on returns by product category to 25 store managers in a 15-minute monthly slot.
• Created a SQL view that replaced 6 copies of the same query across team reports.
• Tested 40 report numbers against the finance system each month and documented every difference.

Skills to list

Certifications and licenses worth listing

• Microsoft Certified: Power BI Data Analyst Associate (PL-300): the most useful entry certificate where employers run Microsoft tools.
• Google Data Analytics Professional Certificate: helpful for career changers who need to show structured training; less so once you have analyst experience.
• Tableau Certified Data Analyst: worth it if the job ads you target name Tableau.
• Not required: a degree in a quantitative field, or solid projects, matter more than any certificate.

Length and format

One page. With a year of full-time work, put experience first, then education with a short line of relevant courses, then one project. Keep GPA while you are within two years of graduating if it is 3.5 or above. A two-column layout keeps tools and a certificate visible without crowding your experience.

Common mistakes

• Listing Python, R, SQL, Tableau, Power BI, Looker, SAS and SPSS when you have used two of them properly.
• Course projects described with the dataset’s name only (“Titanic analysis”). Say what you found and why it mattered.
• No mention of data quality. Reconciling, validating and documenting are a big part of the job; show you do them.
• Bullets about “creating reports” with no audience. Who read it, and what did they do with it?
• A dashboard screenshot or chart pasted into the resume. Link to it from your portfolio instead.