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Data Analyst resume example

Data analyst resumes win on one idea: you turn data into decisions. Show the tools (SQL, Excel, Power BI or Tableau, Python), and then show what the business did differently because of your analysis.

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Why this resume works

  • Every bullet starts with a verb and ends with a result, most with a number.
  • The skills a data analyst job post asks for appear in the Skills section and again inside the bullets.
  • A single, standard layout (Classic Standard) that applicant tracking systems read top to bottom.
  • Standard headings (Summary, Work Experience, Education, Skills) so the ATS files each part correctly.

Maya Thompson

Data Analyst

maya.thompson@email.com | +1 512 555 0193 | Austin, TX | linkedin.com/in/mayathompson

Professional Summary

Data analyst with 3 years of experience in retail and e-commerce. Writes SQL every day, builds Power BI dashboards used by leadership, and uses Python for cleaning and forecasting. Known for turning messy data into clear recommendations.

Work Experience

Greenleaf Grocers

2023 – Present

Data Analyst

  • Built a Power BI sales dashboard for 120 stores that replaced 15 weekly Excel reports.
  • Found a pricing gap in 300 products through SQL basket analysis; the fix added $1.2M in yearly revenue.
  • Forecast weekly demand in Python, cutting fresh-food waste by 14%.
  • Trained 25 store managers to read and filter their own reports.

Clickmart

2021 – 2023

Junior Data Analyst

  • Analyzed A/B tests on the checkout page; recommended changes raised conversion by 6%.
  • Automated a monthly marketing report with SQL and Excel Power Query, saving 2 days of work each month.
  • Cleaned and merged 3 customer databases, removing 40,000 duplicate records.

Education

Texas State University

San Marcos, TX

B.S., Statistics

2017 – 2021

Skills

Analysis: SQL, Excel (Power Query, pivot tables, XLOOKUP), Python (pandas), statistics, A/B testing

Visualization: Power BI, Tableau, Looker Studio

Data: PostgreSQL, BigQuery, Snowflake, data cleaning, ETL

Certificates

Microsoft Certified: Power BI Data Analyst Associate, Microsoft

2023

Example data analyst resume · Classic Standard template · made-up person

Data Analyst resume summary examples

Two or three lines at the top: your years of experience, your strongest skills, and the result you are known for.

This example

Data analyst with 3 years of experience in retail and e-commerce. Writes SQL every day, builds Power BI dashboards used by leadership, and uses Python for cleaning and forecasting. Known for turning messy data into clear recommendations.

Entry level

Data analyst with a statistics degree and the Google Data Analytics Certificate. Built 3 portfolio dashboards in Tableau and SQL on public data, including a city transit analysis viewed 2,000 times. Ready to turn data into answers for a business team.

Experienced

Senior data analyst with 7 years of experience leading analytics for marketing and product teams. Owns the KPI framework, mentors 3 analysts, and has shaped pricing and retention decisions worth over $5M a year.

Write your own with the free summary generator →

Data Analyst resume bullet points

Use them as a pattern, not a copy: swap in your own numbers. If you don't have a number, describe the before and after.

  • Built a Power BI dashboard for 120 stores that replaced 15 manual weekly reports.

  • Found a pricing gap through SQL basket analysis that added $1.2M in yearly revenue.

  • Forecast weekly demand in Python, reducing fresh-food waste by 14%.

  • Analyzed checkout A/B tests and recommended changes that raised conversion by 6%.

  • Automated a monthly report with SQL and Power Query, saving 2 working days each month.

  • Cleaned and merged 3 customer databases, removing 40,000 duplicate records.

  • Defined 12 KPIs with the marketing team so every report used the same numbers.

  • Presented findings to the leadership team every quarter, leading to 2 new product lines.

Turn your own duties into bullets with the free bullet point generator →

Skills and ATS keywords for a data analyst resume

Skills that often appear in data analyst job posts. Add only the ones you really have, in the same words the post uses, and check every job post for its own.

  • SQL
  • Excel
  • Power BI
  • Tableau
  • Python
  • pandas
  • Data visualization
  • Dashboards
  • Data cleaning
  • Statistics
  • A/B testing
  • KPIs
  • ETL
  • BigQuery
  • Snowflake
  • Data modeling
  • Reporting
  • Stakeholder communication
  • Forecasting
  • Business intelligence
Data Analyst cover letter example →See which keywords your resume is missing for a real job →

How to write a data analyst resume

  1. 01

    Show the decision, not only the dashboard

    "Built a dashboard" is common. "Built a dashboard that showed X, and the team changed Y" is rare. End your best bullets with the business result.

  2. 02

    Name your exact tools

    Write "Power BI" or "Tableau", "PostgreSQL" or "BigQuery". Job posts filter for specific tools, and "data visualization software" matches none of them.

  3. 03

    Add a portfolio if you're starting out

    Two or three public projects on Tableau Public, GitHub or a personal site show your work far better than a list of courses.

  4. 04

    Mention who you worked with

    Analysts are hired to help other teams. A line about presenting to leadership or working with marketing shows you can communicate results.

Data Analyst resume, section by section

Header

Name, "Data Analyst", contact details and LinkedIn. If you have public work on Tableau Public, GitHub or a portfolio site, link it here; analysts starting out especially benefit from showing real dashboards.

Summary

Maya's summary names her industries (retail and e-commerce), the tools she uses every day (SQL, Power BI, Python) and how she's seen at work: someone who turns messy data into clear recommendations. Three sentences, all matched to what analyst job posts ask for.

Work experience

Her best bullets end with a business result: a SQL basket analysis that found a pricing gap worth $1.2M a year, a demand forecast that cut fresh-food waste by 14%. The dashboard bullet works because it says what it replaced (15 weekly Excel reports), and training 25 store managers shows she can explain her work.

Skills

Grouped into analysis, visualization and data platforms, with specifics: Power Query, pivot tables and XLOOKUP for Excel; pandas for Python; BigQuery and Snowflake for data. Specific tools beat generic words like "data analysis" every time.

Certification

A tool certification like Microsoft's Power BI Data Analyst helps when the job uses that tool. One line is enough.

Education

A degree in statistics, economics, math, engineering or business is common, but not required. Keep it to one line under experience once you have a year or two of work.

Entry-level to senior data analyst resume bullet points

Entry-level analyst (0–2 years)

  • Answer 30+ ad hoc SQL requests a month from marketing and finance.
  • Built an Excel model to track weekly sales against target for 40 regional reps.
  • Cleaned survey data from 8,000 customers and summarized the top reasons for returns.
  • Moved 6 recurring reports into Looker Studio, saving the team about 5 hours a week.

Data analyst (3–5 years)

  • Own pricing analytics for a 3,000-product catalog, reviewed weekly with the category team.
  • Ran a cohort analysis showing first-month churn came from one delivery region; fixes cut churn by 9%.
  • Built dbt models in Snowflake so 12 dashboards report the same revenue number.
  • Run around 20 A/B tests a year with product, checking sample size and significance before decisions.

Senior / lead analyst (6+ years)

  • Lead 4 analysts supporting marketing, operations and finance.
  • Set the company's KPI definitions and data dictionary, used in every leadership review.
  • Built the marketing mix analysis that moved $2M of spend from display to search with no drop in sales.
  • Train around 60 managers a year to build their own reports in Power BI.

Mistakes to avoid on a data analyst resume

  • Every tool at the same level

    SQL, R, Python, SAS, Tableau, Power BI and Excel listed side by side suggests you're expert in all of them. Lead with the ones you use daily and describe the rest honestly.

  • Writing for analysts, not managers

    "Built a random forest with 0.82 AUC" means little to a hiring manager in marketing. Say what the analysis told the business and what it did next.

  • Only describing data cleaning

    Cleaning is real work, but on its own it sounds like a means without an end. Say what the clean data made possible: a report, a forecast, a decision.

  • Precision that looks made up

    "Improved efficiency by 37.42%" invites doubt. Round to sensible figures and be ready to explain how you measured them.

Key takeaways

  • End your best bullets with the decision or result the business got.
  • Name your exact tools: SQL, Excel functions, Power BI or Tableau, Python.
  • Say who used your dashboards and what they replaced.
  • Link public work if you're early in your career.

Questions about data analyst resumes

What skills should a data analyst put on a resume?
SQL and Excel first, since nearly every post asks for them. Then one BI tool (Power BI or Tableau), Python or R if you use it, and statistics. Add the domain you know, such as retail or finance.
Are certificates like Google Data Analytics worth listing?
Yes, especially when you're changing careers or just starting. Put them under Certificates and back them up with a project that uses the same skills.
How do I write a data analyst resume with no experience?
Lead with a Projects section: pick public datasets, answer a real question with SQL and a dashboard, and write each project as a bullet with the finding.
How do I show the impact of a dashboard?
Say who uses it, how often, and what it replaced or changed: "used by 120 store managers every Monday, replacing 15 Excel reports". If a decision came from it, add that too.
Should I list Python if I only use it a little?
Yes, with an honest description of what you use it for, like "Python (pandas) for cleaning and merging data". Interviewers ask about anything on the page, so describe the level you can defend.

Sources

Duties, pay, education and job outlook for data scientists in the US: U.S. Bureau of Labor Statistics, Occupational Outlook Handbook.

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