Mid-Level Data Analyst Resume Example
By the middle of a data career, employers look for analysis that changed a decision and the judgment to know which numbers matter. This example shows a marketplace analyst who owns her area, designs tests and checks the work of newer analysts.
Mid career · Last reviewed 5 November 2026 · 2 min read · How we write these
Slate puts the dates in a timeline beside each role.
Why this example works
- The returns result names the cause found, the change the business made and the rate before and after, so the analysis is clearly the reason.
- The delivery test shows judgment: the winning threshold comes with a check that orders did not fall.
- Moving reports into BigQuery and dbt shows the analyst improving how the team works, not only answering questions.
- Reviewing junior analysts' work signals readiness for a lead role without claiming the title.
How to write your own data analyst resume
- Lead with one analysis that changed a business decision, and give the measure before and after with the time it took to move.
- When you designed an experiment, state how long it ran, what you protected against and what the business chose afterwards.
- Name your data stack in the order the data flows, from warehouse to transformation to dashboard.
- Say who reads your reports and how often; a weekly audience of category heads says more than a count of dashboards.
- If you review other analysts' queries, include it, since it shows you are ready to lead without overstating your title.
Skills worth including
Analysis
SQL, Python, A/B testing, Statistics, Forecasting, Root cause analysis
Data stack
BigQuery or Snowflake, dbt, Data modeling, Excel
Reporting
Power BI, Tableau, Written insight notes, Stakeholder reporting
Only list what is true for you. A skill you cannot talk about in an interview does not help.
Common questions
Once the jobs are solid, when does a student project earn its place?
Drop them once your jobs show the same skills. Keep a personal project only if it proves something your work does not, such as a public dataset analyzed in Python.
What if my analysis informed a call that a category head signed off?
Say what your analysis found, who acted on it and what changed. A line such as 'category managers added size guides after the analysis' is honest and still shows the result.
Is a Power BI certificate worth adding at this stage?
It helps when the advert names Power BI. Microsoft's PL-300 exam leads to the Power BI Data Analyst Associate certificate, which is renewed each year through a free online assessment, so keep the year current.