Salary for Senior-level / Expert Data Operations Engineer in United States during 2023

Salary details

The average senior-level / expert Data Operations Engineer salary lies between USD 125,000 and USD 238,530 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

Salary trend

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

The three most common job tag items assiciated with senior-level / expert Data Operations Engineer job listings are DataOps, Python and SQL. 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:

DataOps | 17 jobs Python | 16 jobs SQL | 15 jobs AWS | 14 jobs Computer Science | 11 jobs Engineering | 10 jobs Security | 10 jobs Privacy | 10 jobs ETL | 9 jobs Hadoop | 8 jobs Spark | 8 jobs Architecture | 8 jobs Snowflake | 8 jobs Pipelines | 8 jobs Machine Learning | 7 jobs GCP | 7 jobs Big Data | 6 jobs Azure | 6 jobs Data management | 6 jobs RDBMS | 6 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Data Operations Engineer job listings are Career development, Health care and Parental leave. 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:

Career development | 15 jobs Health care | 12 jobs Parental leave | 10 jobs Flex vacation | 10 jobs Flex hours | 9 jobs Startup environment | 9 jobs Insurance | 9 jobs 401(k) matching | 7 jobs Competitive pay | 7 jobs Equity / stock options | 6 jobs Team events | 6 jobs Medical leave | 6 jobs Home office stipend | 6 jobs Salary bonus | 3 jobs Wellness | 2 jobs Fitness / gym | 2 jobs Fertility benefits | 2 jobs Lunch / meals | 1 jobs Transparency | 1 jobs Snacks / Drinks | 1 jobs

Salary Composition

The salary for a Senior-level or Expert Data Operations Engineer in the United States typically comprises several components. The fixed base salary is the largest portion, often accounting for 70-80% of the total compensation package. Bonuses, which can be performance-based or tied to company profits, usually make up 10-20% of the salary. Additional remuneration might include stock options, especially in tech companies, and other benefits such as health insurance, retirement contributions, and paid time off. The exact composition can vary significantly depending on the region, industry, and company size. For instance, tech hubs like Silicon Valley or New York City might offer higher base salaries and more substantial stock options, while smaller companies might compensate with higher bonuses or unique perks.

Increasing Salary Further

To increase your salary beyond the current median, consider pursuing leadership roles such as Data Operations Manager or Director of Data Engineering. These positions often come with higher pay scales. Additionally, specializing in high-demand areas like machine learning operations (MLOps) or cloud data engineering can make you more valuable. Networking within industry circles and attending relevant conferences can also open doors to higher-paying opportunities. Another strategy is to negotiate your salary by leveraging offers from other companies, provided you are willing to consider a job change.

Educational Requirements

Most Senior-level Data Operations Engineers hold at least a bachelor's degree in computer science, data science, engineering, or a related field. However, a master's degree or even a Ph.D. can be advantageous, especially for roles in cutting-edge industries or research-focused companies. Advanced degrees often provide deeper technical knowledge and can be a differentiator in competitive job markets.

Helpful Certifications

Certifications can bolster your credentials and demonstrate expertise in specific areas. Some valuable certifications include:

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

These certifications can validate your skills in data management, cloud platforms, and big data technologies, making you a more attractive candidate for senior roles.

Required Experience

Typically, a Senior-level Data Operations Engineer is expected to have 7-10 years of experience in data engineering, data operations, or related fields. This experience should include a strong track record of managing data pipelines, optimizing data workflows, and implementing data governance practices. Experience with cloud platforms, big data technologies, and programming languages like Python or SQL is often essential. Leadership experience, such as managing teams or projects, can also be crucial for senior roles.

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