$60k - $145k
in the life sciences industry. The Migration Consultant will lead customer migration implementations by providing expertise with data and document content migration, Vault API, Vault migration tools, and Vault Platform b…
Engineering & IT · Kansas City, MO
Data Analyst jobs in Kansas City, MO
Data analysts answer business questions with data — writing SQL, building dashboards, and turning metrics into clear recommendations for teams that need to make a call.
375
Open roles today
$25–$61/hr
Typical pay range
$87k
Median, full-time
3
Fresh in this list
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01
Open data analyst roles
6 shown of 375 · sorted by freshness
We re Hiring: Entry-Level / Junior / Mid-Level Business Analyst & Data Analyst Are you ready to kick-start or grow your career as a Business Analyst or Data Analyst? Join Midwestern IT and work on exciting projects while…
dependent life, group term life, and AD&D. JOB SUMMARY The Senior Analyst position is a key role within the IPFS corporate finance... ...closely with the AndDone (PayFac), Corporate Accounting, Finance, and Data organiza…
Job Description Job Description Data Engineer/ Analyst Position Summary The Data Engineer/Data Analyst is responsible for designing, building and maintaining our cloud-based data ecosystem while also delivering high‑valu…
team of dreamers and doers who are pushing the boundaries of what's possible. And we want YOU to be a part of it. Role: Data Analyst Experience: 5+ Years of experience Location: Hyderabad Summary Data & Analytics functio…
$55 - $65 per hour
Overview Essmann, a specialist in high-quality custom cabinetry, furniture, and millwork, is seeking a meticulous and insightful Data Analyst to join our team. With a strong reputation for quality craftsmanship and tailo…
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What data analysts earn in Kansas City
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $25–$36 | $52k–$75k |
| Mid level | $36–$48 | $75k–$99k |
| Senior | $45–$61 | $94k–$127k |
Adjusted for the Kansas City market from national ranges.
03
What employers ask for
The skills these listings keep naming
SQLExcel / Google SheetsTableau, Power BI, or LookerBasic statisticsPython or R (a plus)Data cleaningDashboard designPresenting findings clearlyBusiness domain knowledge
04
Interview questions worth rehearsing
With the thing the interviewer is actually listening for
A metric dropped 15% week over week. How do you investigate?
Segment first — by platform, region, source — and check for data issues before assuming a real change. A methodical decomposition is exactly what they want.
Walk me through a dashboard or report you built that people actually used.
Focus on the decision it supported and how you designed for the audience. Adoption is the success metric, not chart count.
How comfortable are you with SQL? Describe a complex query you wrote.
Mention joins, window functions, or CTEs in the context of a real question. Expect a live exercise, so pick an example you can reconstruct.
A stakeholder wants data that supports a conclusion they already hold. What do you do?
Show that you present what the data says, frame caveats respectfully, and stay useful without becoming a rubber stamp.
How do you check whether your analysis is correct before sharing it?
Talk about sanity checks against known totals, replicating with a second method, and having someone review the logic. Self-QA habits separate reliable analysts.
Correlation versus causation — give a business example where it matters.
Use a concrete case, like ice cream and sunburn or a marketing example, and mention what would move you toward causal confidence, such as an experiment.
05
Resume tips that move the needle
For data analysts specifically — generic advice costs you here
01
Tie each analysis to the decision or dollar outcome it drove — 'identified churn segment worth $400K in retained revenue' is the format that works.
02
List SQL first and honestly grade your level; it is the single most tested skill for this role.
03
Name the BI tools you have shipped dashboards in, and how many people relied on them.
04
Show domain context (e-commerce, SaaS, healthcare) because analysts are hired into a business, not just a toolset.
05
A small portfolio of public analyses with clear write-ups can offset limited job experience.
06
Where this role goes
Typical progression
01
Junior Data Analyst
02
Data Analyst
03
Senior Data Analyst
04
Analytics Manager
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