The Analyst Board

US data careers

Data analyst roles

Data analysts answer business questions with evidence. Depending on the team, that can mean cleaning data, writing SQL, building a dashboard, investigating a change in performance, or presenting a recommendation. Use the current openings below to see which mix of technical depth and business ownership employers actually request.

These openings focus on employers hiring in the United States, whether the role is on-site, hybrid, or available remotely within stated US locations.

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SQL · Excel · Business insight

Use this guide

Compare career paths, skills, and current openings

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Fast job-description check

Highlight every verb in the responsibilities. If most verbs are build, maintain, refresh, the role is reporting-heavy. If they are investigate, test, recommend, it is insight-heavy. If they are model, automate, engineer, expect greater technical depth. This quick check helps you compare roles with identical titles.

Which analytical questions energize you?

Open the type of question you would be happiest answering every week.

What happened, and where is the problem?

General Data Analyst, Operations Analyst, and Performance Analyst roles often focus on descriptive analysis, recurring KPIs, anomaly investigation, and root causes. Excel, SQL, dashboards, and concise communication form the core toolkit.

Why did users behave this way, and what should we test?

Explore Product Analyst, Growth Analyst, or Customer Insights roles. These may add event data, funnels, cohorts, experimentation, and closer work with product or marketing teams.

How can we make the data itself more reliable and reusable?

Look for Senior Data Analyst, Analytics Engineer, or BI Developer roles. Data models, documentation, reusable transformations, testing, and governance carry more weight.

What US data analyst roles expect

SQL, spreadsheets, and a visualization tool such as Power BI or Tableau.
Data cleaning, validation, descriptive statistics, and careful metric definitions.
Turning an open-ended question into a scoped analysis.
Explaining conclusions, caveats, and recommended action.
Python or R for some roles, especially when automation or deeper statistical analysis is involved.

Compare BI and reporting jobs or browse remote analyst roles. Hiring a data analyst in the US? Reach candidates comparing technical depth, business ownership, and work arrangements — post a job.

Data analyst job FAQ

Do data analysts need Python?

Not every role requires it. SQL, Excel, and a BI tool cover many business-facing positions. Python becomes more valuable for repeatable data preparation, larger datasets, advanced statistics, or automation.

What should a data analyst portfolio show?

Show the question, data-quality checks, reasoning, decision, and limitations—not just a polished chart. A small project with a credible recommendation is usually more persuasive than a large dashboard with no business context.

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