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

Salary details

The average mid-level / intermediate Data Quality Analyst salary lies between USD 65,000 and USD 95,000 globally. 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.

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 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 policy and the individual’s performance. In larger tech companies or financial institutions, bonuses might be more substantial compared to smaller firms. Additional remuneration like stock options is more common in tech startups or large tech companies, especially in regions like Silicon Valley. In contrast, companies in other regions or industries might offer less in terms of bonuses and stock options, focusing more on the base salary.

Steps to Increase 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 data engineering. Proficiency in tools like Python, R, SQL, and data visualization software can make you more valuable.
• Certifications: Obtain relevant certifications that can enhance your expertise and marketability.
• Networking: Engage with industry professionals through conferences, workshops, and online platforms to learn about new opportunities and trends.
• Advanced Education: Consider pursuing a master’s degree in data science, analytics, or a related field to open up 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 and interpretation skills. A strong foundation in data management, statistical analysis, and database systems is essential.

Helpful Certifications

Several certifications can be beneficial for a Data Quality Analyst:

• Certified Data Management Professional (CDMP): Focuses on data management skills.
• Microsoft Certified: Azure Data Scientist Associate: Useful for those working with Microsoft Azure.
• SAS Certified Data Scientist: Offers a comprehensive understanding of data manipulation and analysis.
• IBM Data Science Professional Certificate: Provides a broad overview of data science tools and techniques.

These certifications can help demonstrate your commitment to the field and enhance your technical skills.

Required Experience

Typically, a Mid-level Data Quality Analyst is expected to have 2-5 years of experience in data analysis, data management, or a related field. Experience with data quality tools, data governance, and data cleansing processes is often required. Familiarity with industry-specific data standards and regulations can also be advantageous.

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