Data Operations Engineer Salary in United States during 2024

Salary details

The average Data Operations Engineer salary lies between USD 102,424 and USD 135,000 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: Nov. 10, 2024

Salary trend

Top 20 Job Tags for Data Operations Engineer roles

The three most common job tag items assiciated with Data Operations Engineer job listings are DataOps, Python 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:

DataOps | 52 jobs Python | 36 jobs SQL | 36 jobs Pipelines | 33 jobs Engineering | 31 jobs Data pipelines | 25 jobs Computer Science | 24 jobs ETL | 21 jobs Architecture | 18 jobs Data quality | 18 jobs AWS | 17 jobs Airflow | 17 jobs Agile | 17 jobs GCP | 15 jobs Machine Learning | 14 jobs Security | 14 jobs Tableau | 13 jobs Testing | 13 jobs dbt | 13 jobs CI/CD | 12 jobs

Top 20 Job Perks/Benefits for Data Operations Engineer roles

The three most common job benefits and perks assiciated with Data Operations 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 | 35 jobs Health care | 25 jobs Flex hours | 18 jobs Equity / stock options | 17 jobs Competitive pay | 12 jobs Flex vacation | 11 jobs Startup environment | 11 jobs Parental leave | 10 jobs Wellness | 10 jobs 401(k) matching | 8 jobs Team events | 8 jobs Salary bonus | 7 jobs Medical leave | 6 jobs Insurance | 6 jobs Fitness / gym | 5 jobs Home office stipend | 5 jobs Transparency | 3 jobs Gear | 2 jobs Conferences | 2 jobs Lunch / meals | 1 jobs

Salary Composition

The salary for a Data Operations Engineer in the AI/ML/Data Science field typically consists of a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually makes up the majority of the total compensation package. Bonuses can vary significantly depending on the company's performance, individual performance, and industry standards. In tech hubs like Silicon Valley, bonuses might be more substantial compared to other regions. Additional remuneration can include stock options, especially in startups or tech companies, and benefits such as health insurance, retirement plans, and paid time off. Larger companies might offer more comprehensive benefits packages, while smaller companies might compensate with higher equity stakes.

Increasing Salary

To increase your salary from the position of a Data Operations Engineer, consider the following steps:

• Skill Enhancement: Continuously update your skills in the latest AI/ML technologies and tools. Specializing in a niche area can make you more valuable.
• Advanced Education: Pursuing a master's degree or Ph.D. in a related field can open up higher-paying opportunities.
• Leadership Roles: Transitioning into managerial or leadership roles can significantly increase your earning potential.
• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or roles.
• Certifications: Obtaining relevant certifications can demonstrate your expertise and commitment to the field, potentially leading to salary increases.

Educational Requirements

Most Data Operations Engineer positions require at least a bachelor's degree in computer science, data science, engineering, or a related field. Some employers may prefer candidates with a master's degree, especially for more advanced roles. A strong foundation in mathematics, statistics, and programming is essential. Courses in data management, machine learning, and cloud computing can also be beneficial.

Helpful Certifications

Certifications can enhance your resume and demonstrate your expertise. Some valuable certifications for a Data Operations Engineer include:

• Certified Data Management Professional (CDMP)
• AWS Certified Data Analytics
• Google Professional Data Engineer
• Microsoft Certified: Azure Data Engineer Associate
• Cloudera Certified Data Engineer

These certifications can help you stand out in the job market and may lead to better job opportunities and higher salaries.

Required Experience

Typically, employers look for candidates with 3-5 years of experience in data operations, data engineering, or a related field. Experience with data management systems, cloud platforms, and data processing frameworks is often required. Familiarity with programming languages such as Python, SQL, and Java, as well as experience with big data technologies like Hadoop or Spark, is also commonly expected.

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