Salary for Senior-level / Expert Data Quality Engineer in United States during 2024

Salary details

The average senior-level / expert Data Quality Engineer salary lies between USD 111,900 and USD 138,800 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: Nov. 17, 2024

Top 20 Job Tags for Senior-level / Expert Data Quality Engineer roles

The three most common job tag items assiciated with senior-level / expert Data Quality Engineer job listings are Data quality, SQL and Python. 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 | 38 jobs SQL | 35 jobs Python | 29 jobs Engineering | 27 jobs Testing | 25 jobs ETL | 23 jobs Agile | 22 jobs Pipelines | 20 jobs Computer Science | 18 jobs AWS | 15 jobs Data Warehousing | 14 jobs Data pipelines | 14 jobs Data management | 14 jobs Security | 13 jobs Architecture | 12 jobs GCP | 12 jobs Data governance | 12 jobs Big Data | 11 jobs Git | 11 jobs APIs | 11 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Data Quality Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert Data Quality Engineer job listings are Career development, Health care and Flex hours. 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 | 24 jobs Health care | 15 jobs Flex hours | 13 jobs Team events | 9 jobs Startup environment | 7 jobs Salary bonus | 7 jobs Equity / stock options | 6 jobs Flat hierarchy | 6 jobs Home office stipend | 6 jobs Parental leave | 5 jobs Flex vacation | 5 jobs Gear | 5 jobs Competitive pay | 5 jobs Yoga | 4 jobs Insurance | 3 jobs 401(k) matching | 2 jobs Wellness | 2 jobs Transparency | 2 jobs Relocation support | 2 jobs Medical leave | 2 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Data Quality Engineer can vary significantly based on factors such as region, industry, and company size. Typically, the salary is divided into three main components:

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation package. For a role like this, the base salary can range from 70% to 85% of the total compensation.

• Bonus: Bonuses are often performance-based and can vary widely. They might be tied to individual performance, team performance, or company-wide success. In tech hubs like Silicon Valley, bonuses can be more substantial, sometimes making up 10% to 20% of the total compensation.

• Additional Remuneration: This includes stock options, profit sharing, and other incentives. In larger tech companies or startups, stock options can be a significant part of the compensation package, potentially accounting for 5% to 15% of the total remuneration.

Increasing Salary

To increase your salary further from this position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging technologies and methodologies in AI/ML and data science. Specializing in niche areas can make you more valuable.

• Leadership Roles: Transitioning into managerial or leadership roles can significantly boost your salary. This might involve leading a team of data engineers or taking on project management responsibilities.

• Industry Shift: Some industries, like finance or healthcare, may offer higher salaries for data quality engineers due to the critical nature of data in these fields.

• Networking and Visibility: Attend industry conferences, contribute to open-source projects, or publish articles to increase your visibility and network within the industry.

Educational Requirements

Most Senior-level Data Quality Engineer positions require at least a bachelor's degree in a related field such as Computer Science, Information Technology, or Data Science. However, a master's degree or even a Ph.D. can be advantageous, especially for roles that require a deep understanding of data science and machine learning principles.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise:

• Certified Data Management Professional (CDMP): This certification is highly regarded in the data management field.

• AWS Certified Big Data – Specialty: Useful if you are working with AWS technologies.

• Google Professional Data Engineer: Beneficial for roles involving Google Cloud Platform.

• Certified Information Systems Auditor (CISA): This can be useful if your role involves auditing data quality processes.

Experience Requirements

Typically, a Senior-level Data Quality Engineer is expected to have at least 5 to 10 years of experience in data engineering, data quality, or related fields. Experience with data governance, data warehousing, and ETL processes is often required. Familiarity with data quality tools and frameworks, as well as experience in managing data quality projects, is also crucial.

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