Salary for Mid-level / Intermediate Data Quality Engineer in United States during 2024

Salary details

The average mid-level / intermediate Data Quality Engineer salary lies between USD 80,000 and USD 132,300 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: Dec. 22, 2024

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

The three most common job tag items assiciated with mid-level / intermediate Data Quality Engineer job listings are Data quality, Engineering and SQL. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

Data quality | 26 jobs Engineering | 19 jobs SQL | 18 jobs Python | 16 jobs Testing | 14 jobs Computer Science | 12 jobs Power BI | 8 jobs Pipelines | 8 jobs Data analysis | 8 jobs Java | 8 jobs NoSQL | 7 jobs Statistics | 7 jobs ETL | 6 jobs Tableau | 6 jobs Azure | 6 jobs MongoDB | 5 jobs AWS | 5 jobs Research | 5 jobs Data pipelines | 5 jobs PostgreSQL | 5 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Data Quality Engineer job listings are Career development, Flex hours and Startup environment. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 17 jobs Flex hours | 9 jobs Startup environment | 9 jobs Health care | 8 jobs Flex vacation | 7 jobs Equity / stock options | 6 jobs Competitive pay | 6 jobs Wellness | 5 jobs Medical leave | 3 jobs 401(k) matching | 2 jobs Parental leave | 2 jobs Transparency | 2 jobs Salary bonus | 2 jobs Relocation support | 1 jobs Insurance | 1 jobs Home office stipend | 1 jobs

Salary Composition for a Mid-level Data Quality Engineer

The salary for a Mid-level Data Quality Engineer in the United States typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The base salary often constitutes the majority of the total compensation package, usually ranging from 70% to 85%. Performance bonuses can vary significantly depending on the company and industry, often making up 10% to 20% of the total compensation. Additional remuneration, such as stock options, profit-sharing, or comprehensive benefits packages, can account for the remaining 5% to 10%.

Regional differences can also impact salary composition. For instance, tech hubs like San Francisco or New York may offer higher base salaries and stock options due to the competitive market, while regions with a lower cost of living might offer more balanced packages with a focus on benefits. Industry and company size also play a role; larger tech companies or those in high-demand sectors may provide more lucrative stock options and bonuses compared to smaller firms or those in traditional industries.

Steps to Increase Salary from This Position

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

• Skill Enhancement: Continuously update your skills in emerging technologies and tools relevant to data quality and data science. Proficiency in machine learning, data visualization, and big data technologies can make you more valuable.

• Advanced Education: Pursuing a master's degree or specialized certifications in data science or related fields can enhance your qualifications and open up higher-paying opportunities.

• Networking and Professional Development: Engage in industry conferences, workshops, and networking events to build connections and learn about new opportunities. Joining professional organizations can also provide access to job openings and career advancement resources.

• Leadership and Management Skills: Developing leadership skills and taking on managerial responsibilities can position you for roles with higher pay scales, such as Data Quality Manager or Director of Data Quality.

Educational Requirements

Most Mid-level Data Quality Engineer positions require at least a bachelor's degree in a relevant field such as Computer Science, Information Technology, Statistics, or Data Science. Some employers may prefer candidates with a master's degree, especially for roles that involve complex data analysis or machine learning tasks. A strong foundation in mathematics and statistics is often essential, as is proficiency in programming languages like Python or R.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise in data quality and related areas. Some valuable certifications include:

• Certified Data Management Professional (CDMP): Offered by DAMA International, this certification validates your knowledge in data management and governance.

• Microsoft Certified: Azure Data Engineer Associate: This certification is beneficial if you work with Microsoft Azure and need to demonstrate your skills in data engineering and quality.

• AWS Certified Data Analytics – Specialty: Useful for those working with AWS, this certification focuses on data analytics and quality in cloud environments.

Experience Requirements

Typically, a Mid-level Data Quality Engineer is expected to have 3 to 5 years of experience in data quality, data analysis, or a related field. Experience with data quality tools, data governance frameworks, and data management practices is crucial. Familiarity with data warehousing, ETL processes, and data modeling can also be advantageous.

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