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

Salary details

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

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 typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is often the largest component, accounting for 70-80% of the total compensation package. Bonuses can vary significantly depending on the company's performance and individual contributions, usually ranging from 10-20% of the base salary. Additional remuneration, such as stock options, can be a significant part of the package in startups or large tech firms, potentially adding another 10-20% to the total compensation. The composition can vary by region, with tech hubs like Silicon Valley offering higher equity components, while regions with a lower cost of living might offer higher base salaries. Industry also plays a role; for instance, finance and healthcare sectors might offer higher bonuses compared to other industries.

Increasing Salary Further

To increase your salary from this position, consider pursuing leadership roles such as Data Operations Manager or Director of Data Engineering. These roles often come with higher compensation packages. 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 conferences can also open up opportunities for higher-paying roles. Another strategy is to negotiate your salary during performance reviews by showcasing your contributions and the impact of your work on the company's bottom line.

Educational Requirements

Most Senior-level Data Operations Engineer positions require 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 in competitive markets or for roles in cutting-edge industries. Advanced degrees often provide deeper knowledge and research experience, which can be crucial for tackling complex data challenges.

Helpful Certifications

Certifications can enhance 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 more attractive to potential employers.

Required Experience

Typically, a Senior-level Data Operations Engineer is expected to have 5-10 years of experience in data engineering, data operations, or related fields. This experience should include hands-on work with data pipelines, ETL processes, and data warehousing solutions. Experience with cloud platforms like AWS, Azure, or Google Cloud is often required, as well as proficiency in programming languages such as Python, SQL, and Java.

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