Salary for Mid-level / Intermediate Data Quality Analyst in United States during 2023

Salary details

The average mid-level / intermediate Data Quality Analyst salary lies between USD 65,000 and USD 95,000 in the United States. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Oct. 28, 2024

Top 20 Job Tags for Mid-level / Intermediate Data Quality Analyst roles

The three most common job tag items assiciated with mid-level / intermediate Data Quality Analyst job listings are Data quality, Excel and Machine Learning. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

Data quality | 13 jobs Excel | 5 jobs Machine Learning | 4 jobs SQL | 4 jobs Engineering | 4 jobs Research | 3 jobs Security | 3 jobs Data governance | 3 jobs NLP | 2 jobs Economics | 2 jobs Testing | 2 jobs ML models | 2 jobs Agile | 2 jobs SAS | 2 jobs Statistics | 2 jobs Data analysis | 2 jobs Data management | 2 jobs Computer Science | 2 jobs Pharma | 2 jobs Python | 1 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Data Quality Analyst roles

The three most common job benefits and perks assiciated with mid-level / intermediate Data Quality Analyst job listings are Health care, Career development and Startup environment. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:

Health care | 4 jobs Career development | 4 jobs Startup environment | 4 jobs Flex hours | 3 jobs Competitive pay | 3 jobs Parental leave | 2 jobs Medical leave | 2 jobs Insurance | 2 jobs Unlimited paid time off | 2 jobs 401(k) matching | 1 jobs Equity / stock options | 1 jobs Flex vacation | 1 jobs Flat hierarchy | 1 jobs Team events | 1 jobs

Salary Composition

The salary for a Mid-level Data Quality Analyst in the United States typically consists of a base salary, performance bonuses, and sometimes additional remuneration such as stock options or profit-sharing. The base salary is the fixed component and usually makes up the majority of the total compensation package. Performance bonuses can vary significantly depending on the company’s policies and the individual’s performance. Additional remuneration like stock options or profit-sharing is more common in larger tech companies or startups, where they are used as incentives to align employee interests with company growth.

Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job markets. Industry can also affect salary composition, with sectors like finance or healthcare potentially offering higher bonuses. Company size is another factor; larger companies might offer more comprehensive benefits packages, while smaller companies might offer higher base salaries to attract talent.

Increasing Salary

To increase your salary from a Mid-level Data Quality Analyst position, consider the following strategies:

• Skill Enhancement: Acquire advanced skills in data analysis, machine learning, or programming languages like Python and R. Specializing in a niche area can make you more valuable.
• Certifications: Obtain relevant certifications that can boost your credentials and demonstrate your expertise.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Advanced Education: Pursue further education, such as a master’s degree in data science or a related field, to qualify for higher-level positions.
• Performance Excellence: Consistently exceed performance expectations to position yourself for promotions and salary increases.

Educational Requirements

Most Mid-level Data Quality Analyst positions require at least a bachelor’s degree in a relevant field such as computer science, information technology, statistics, or mathematics. Some employers may prefer candidates with a master’s degree, especially for roles that require more complex data analysis skills. A strong foundation in data management, statistical analysis, and database systems is essential.

Helpful Certifications

Certifications can enhance your qualifications and make you more competitive in the job market. Some valuable certifications for a Data Quality Analyst include:

• Certified Data Management Professional (CDMP)
• Microsoft Certified: Azure Data Scientist Associate
• IBM Data Science Professional Certificate
• SAS Certified Data Scientist
• Google Data Analytics Professional Certificate

These certifications demonstrate your commitment to the field and your proficiency in data quality and analysis tools.

Experience Requirements

Typically, a Mid-level Data Quality Analyst position requires 2-5 years of experience in data analysis, data management, or a related field. Experience with data quality tools, data governance, and data warehousing is often expected. Familiarity with programming languages like SQL, Python, or R, as well as experience with data visualization tools, can be advantageous.

Related salaries

Want to contribute?