Data Analyst
Data Analysts turn messy numbers into decisions leadership can act on.
Don't just read it — play it
Clock in at 9am and make the calls a Data Analyst makes all day. Six decisions, real consequences, a score at 5pm.
What this role really is
Data Analysts answer business questions with data. Someone asks why a number moved; you find the honest answer and explain it to people who don't write SQL. Half the job is technical (querying, cleaning, checking your work) and half is communication — a correct analysis nobody understands changes nothing.
- Investigate why a metric moved
- Build dashboards people actually use
- Write queries against production data
- Present findings to non-technical teams
- Recommend what to do next
What it pays
- Entry level
- $75k–$105k
- Mid career
- $110k–$140k
- Senior
- $150k+
Typically 9–5:30, busier at month and quarter end
Majors that get you here
Entry roles: Data Analyst · Business Analyst · Analytics Intern
Your 9-to-5, hour by hour
A realistic ordinary day — not the highlight reel.
9:00 AM
Dashboard check
You open the daily dashboards, spot that signups dipped 9% yesterday, and flag it in the team channel before anyone else asks.
10:00 AM
Digging in
You write queries slicing the dip by channel, device and region. It's isolated to mobile web in one country — which points at a release, not a market shift.
12:00 PM
Stakeholder request
Marketing wants last quarter's retention by cohort by Thursday. You scope it, push back on the parts that won't be reliable, and agree on what you'll actually deliver.
1:30 PM
Building the analysis
Clean, join, sanity-check. You catch a duplicate-row bug that would have overstated retention by six points.
3:30 PM
Presenting findings
Fifteen minutes with the growth lead: one chart, one sentence conclusion, one recommendation. They approve rolling back the mobile release.
5:00 PM
Documentation
You document the query, add the metric definition to the team wiki so the next person doesn't rebuild it, and close the ticket.
Great for you if
- You get satisfaction from finding the real reason behind a number
- You like explaining complex things simply
- You're careful and hate being wrong in public
Probably not for you if
- You want to build the product itself
- You dislike repetitive data cleaning