Full Time Power Bi Data Analyst information
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$43.3K - $52.5K
7% of jobs
$52.5K - $61.8K
13% of jobs
$62.4K is the 25th percentile. Wages below this are outliers.
$61.8K - $71.1K
18% of jobs
The median wage is $75.4K / yr.
$71.1K - $80.4K
16% of jobs
$80.4K - $89.6K
13% of jobs
$93.1K is the 75th percentile. Wages above this are outliers.
$89.6K - $98.9K
9% of jobs
$98.9K - $108.2K
5% of jobs
$108.2K - $117.5K
9% of jobs
$117.5K - $126.7K
3% of jobs
$126.7K - $136K
2% of jobs
How much do full time power bi data analyst jobs pay per year?
As of Sep 10, 2026, the average yearly pay for full time power bi data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.
Full Time Power BI Data Analysts are professionals who work with data to create reports, dashboards, and visualizations using Microsoft Power BI. They gather, process, and analyze data to help organizations make informed business decisions. Their role typically involves transforming raw data into meaningful insights, ensuring data accuracy, and collaborating with stakeholders to meet reporting needs. As full-time employees, they work regular business hours and are often part of larger analytics or business intelligence teams.
To thrive as a Full Time Power BI Data Analyst, you need strong analytical skills, proficiency in data modeling, and a solid understanding of statistics, typically supported by a degree in computer science, statistics, or a related field. Expertise in Power BI, SQL, and data visualization tools, along with familiarity with databases and possibly DAX or Python, is highly valued. Excellent communication, problem-solving abilities, and attention to detail help you translate complex data into actionable insights for stakeholders. These skills are vital for producing accurate, insightful reports that drive informed business decisions.
A Full Time Power BI Data Analyst often encounters challenges when integrating and transforming data from multiple sources, such as SQL databases, Excel, and cloud platforms. Ensuring data accuracy and consistency can require significant attention to detail, especially when sources have varying formats or incomplete records. Effective communication with stakeholders is also crucial, as understanding business requirements helps in designing meaningful dashboards and reports. Adapting quickly to new data tools and technologies is key to overcoming these challenges and delivering actionable insights.
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