Data Loading Analyst information
See Albuquerque, NM salary details
$47.4K - $55.7K
13% of jobs
$56.2K is the 25th percentile. Wages below this are outliers.
$55.7K - $64.1K
18% of jobs
The median wage is $68K / yr.
$64.1K - $72.4K
16% of jobs
$72.4K - $80.8K
13% of jobs
$83.9K is the 75th percentile. Wages above this are outliers.
$80.8K - $89.2K
9% of jobs
$89.2K - $97.5K
5% of jobs
$97.5K - $105.9K
9% of jobs
$105.9K - $114.2K
3% of jobs
$114.2K - $122.6K
2% of jobs
How much do data loading analyst jobs pay per year?
As of Aug 22, 2026, the average yearly pay for data loading analyst in Albuquerque, NM is $74,502.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,300.00 and $87,400.00 per year, depending on experience, location, and employer.
A Data Loading Analyst is a professional responsible for importing, validating, and managing large sets of data within an organization's databases or systems. They ensure that data from various sources is accurately loaded, transformed, and integrated according to business requirements. Their work helps maintain data integrity, support business intelligence activities, and facilitate smooth data migrations or system updates. Data Loading Analysts often collaborate with data engineers, IT teams, and business analysts to meet organizational data needs.
To thrive as a Data Loading Analyst, you need a solid understanding of data management, ETL (Extract, Transform, Load) processes, and database concepts, often supported by a degree in computer science or a related field. Familiarity with data integration tools such as Informatica or Talend, and proficiency in SQL or other database querying languages, are commonly required. Attention to detail, problem-solving ability, and strong communication skills help ensure data accuracy and effective collaboration with business and IT teams. These skills are essential for maintaining data integrity and supporting informed business decisions.
Data Loading Analysts often encounter challenges such as handling data inconsistencies, meeting tight deadlines for large-scale uploads, and ensuring data accuracy across multiple sources. Collaboration with IT teams and business stakeholders is crucial to resolve discrepancies and validate data mappings. Additionally, adapting to evolving data formats and troubleshooting loading errors are common parts of the role. Proactive communication and strong problem-solving skills can help mitigate these challenges and ensure smooth data integration.
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