Data Analyst Skills for a Resume

Companies hire data analysts to answer business questions with numbers people can trust. Show the tools you query and present with, and prove your value with the decisions your analysis changed.

Updated

14 skills at a glance

Hard skills

What the work takes, how a hiring manager judges each skill, and a bullet point that shows it.

  1. SQL

    Show complexity: window functions, large joins, or the size of the warehouse you query.

    Example bullet pointWrote window-function queries to compare customer lifetime value by acquisition channel over three years of orders.

  2. Python or R

    Show what you automate or analyze with it, beyond what SQL and spreadsheets can do.

    Example bullet pointBuilt an R script that cleans survey responses and produces weighted results in minutes instead of a day.

  3. Dashboards (Tableau, Power BI, Looker)

    Name the tool and show adoption: who uses your dashboards and what they replaced.

    Example bullet pointBuilt a Power BI dashboard of sales against target for store managers, opened daily by 120 people.

  4. Spreadsheets

    Advanced spreadsheet skills still matter. Mention models, lookups or pivot tables others rely on.

    Example bullet pointBuilt a budget-tracking workbook with lookups and pivot tables that finance used for monthly reviews.

  5. Statistics and A/B testing

    Show sound method: sample sizes, significance and how you explained the results.

    Example bullet pointStopped a test from being called early by showing the sample was too small to detect the expected change.

  6. Data modeling (dbt)

    Show reusable models and tests that made data more reliable.

    Example bullet pointBuilt tested dbt models for orders and refunds that became the single source for revenue reports.

  7. Cloud warehouses (Snowflake, BigQuery, Redshift)

    Name the warehouse and any cost or speed improvements you made.

    Example bullet pointCut BigQuery costs by a third by partitioning the events table and rewriting the heaviest scheduled queries.

  8. Data cleaning

    Show the mess you handled and why it mattered.

    Example bullet pointMatched customer records across two systems, removing 8,000 duplicates before a marketing launch.

  9. Forecasting

    Mention the method and how accurate it was in practice.

    Example bullet pointForecast weekly call volumes for the support team, helping them plan staffing two weeks ahead.

Soft skills

Shown through what you did, never claimed as adjectives.

  1. Asking the right question

    Show a request you reshaped into the question that really mattered.

    Example bullet pointTurned a request for a churn report into a study of which onboarding step lost the most customers.

  2. Explaining numbers simply

    Show presentations or summaries that led to a decision.

    Example bullet pointSummed up a pricing analysis on one page with three charts; leadership approved the change the same week.

  3. Skepticism

    Show a number you questioned that turned out to be wrong.

    Example bullet pointQuestioned a sudden jump in sign-ups and traced it to a tracking bug before it reached the board report.

  4. Attention to detail

    Point to the checks that kept your numbers right.

    Example bullet pointReconciled dashboard revenue against the finance ledger every month and closed gaps within a day.

  5. Working with stakeholders

    Show how you worked with teams to define what they needed and delivered results they used.

    Example bullet pointMet sales leaders every month to agree on metric definitions before building their reports.

Licenses and certifications

Give them a section of their own, with who issued each one and the year or expiry date.

  • Google Data Analytics Certificate
  • Microsoft Certified: Power BI Data Analyst Associate
  • Tableau Certified Data Analyst

Keywords from data analyst job postings

Use the ones that are true for you, in your bullet points as well as your skills list.

  • SQL
  • Python
  • Tableau
  • dashboards
  • cohort analysis
  • A/B tests
  • Snowflake
  • dbt
  • reports

Each posting has its own words. Our guide to tailoring your resume to a job description shows how to find them and where to put them.

Where to put your skills

  • In a skills section: a short list of the hard skills the posting names, in its words.
  • In your bullet points: every skill that matters should show up in something you did, with a result. That is where a hiring manager believes it.
  • In your summary: two or three of the skills the job asks for most.

More on choosing them in how to choose and prove the skills on your resume.

Questions

What skills should a data analyst put on a resume?

SQL, Python or R, a dashboard tool, spreadsheets, statistics and A/B testing, data modeling, a cloud warehouse, data cleaning and forecasting, plus asking good questions and explaining numbers simply.

Which dashboard tool should I learn?

The one in the postings you want. Tableau, Power BI and Looker work in similar ways, so experience in one carries over to the others.

How do I show impact as a data analyst?

Name the decision your analysis informed and what happened next: money saved, revenue gained or time freed.

Put them to work

Start from a data analyst resume that already uses these skills, for an invented person, and make it yours in the builder.

Use this exampleRead the data analyst resume example