Senior Metadata Analyst information
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$63.4K - $70.9K
3% of jobs
$70.9K - $78.3K
6% of jobs
$78.3K - $85.8K
9% of jobs
$89.5K is the 25th percentile. Wages below this are outliers.
$85.8K - $93.2K
10% of jobs
$93.2K - $100.7K
13% of jobs
The median wage is $106.5K / yr.
$100.7K - $108.1K
10% of jobs
$108.1K - $115.6K
11% of jobs
$118.4K is the 75th percentile. Wages above this are outliers.
$115.6K - $123K
33% of jobs
$123K - $130.5K
4% of jobs
How much do senior metadata analyst jobs pay per year?
As of Aug 27, 2026, the average yearly pay for senior metadata analyst in the United States is $102,527.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,000.00 and $116,500.00 per year, depending on experience, location, and employer.
A Senior Metadata Analyst is responsible for managing and optimizing metadata, which is data that describes other data, within an organization's systems. They ensure the accuracy, consistency, and integrity of metadata to support data management, discovery, and governance initiatives. Senior Metadata Analysts often collaborate with IT, data governance, and business teams to create metadata standards and processes, and they may also use specialized tools to catalog and maintain metadata repositories.
To thrive as a Senior Metadata Analyst, you need expertise in data management, metadata standards, and information architecture, often supported by a degree in information science or a related field. Familiarity with metadata management tools (such as Collibra or Informatica), data catalog systems, and data governance frameworks is typically required. Strong analytical thinking, attention to detail, and effective communication skills help in collaborating with stakeholders and ensuring data consistency. These skills are crucial for maintaining data quality, enabling efficient data discovery, and supporting organizational data governance initiatives.
A Senior Metadata Analyst frequently works cross-functionally with teams such as data governance, IT, business intelligence, and compliance to ensure metadata standards and best practices are consistently applied. They often facilitate workshops, lead metadata documentation efforts, and provide guidance on data classification to support business needs. Effective collaboration is key, as they help bridge technical and business perspectives, ensuring data assets are discoverable, trustworthy, and aligned with organizational goals.
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