Data Operations Engineer Salary in 2024

Salary details

The average Data Operations Engineer salary lies between USD 102,424 and USD 135,000 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: Nov. 17, 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, 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:

DataOps | 53 jobs SQL | 37 jobs Python | 36 jobs Pipelines | 33 jobs Engineering | 32 jobs Data pipelines | 25 jobs Computer Science | 24 jobs ETL | 21 jobs Data quality | 19 jobs Architecture | 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 | 36 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 for a Data Operations Engineer

The salary composition for a Data Operations Engineer can vary significantly based on factors such as region, industry, and company size. Typically, the salary is divided into three main components: a fixed base salary, a performance-based bonus, and additional remuneration such as stock options or benefits.

• Fixed Base Salary: This is the guaranteed portion of the salary and usually constitutes the majority of the total compensation package. In regions with a high cost of living, such as the San Francisco Bay Area or New York City, the base salary might be higher to compensate for living expenses.

• Performance-Based Bonus: Bonuses are often tied to individual performance, team performance, or company profitability. In tech-heavy industries, bonuses can be a significant part of the compensation, sometimes ranging from 10% to 20% of the base salary.

• Additional Remuneration: This can include stock options, especially in startups or tech companies, as well as benefits like health insurance, retirement contributions, and other perks. Larger companies might offer more comprehensive benefits packages.

Steps to Increase Salary from a Data Operations Engineer Position

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

• Skill Enhancement: Continuously update your skills in AI/ML and data science. Learning new programming languages, tools, or frameworks can make you more valuable.

• Advanced Education: Pursuing a master's degree or specialized certifications can open up higher-paying opportunities.

• Networking: Building a strong professional network can lead to new job opportunities or promotions within your current company.

• Leadership Roles: Aim for leadership or managerial positions, which typically come with higher salaries.

• Industry Shift: Consider moving to industries that pay higher salaries for data roles, such as finance or tech.

Educational Requirements for a Data Operations Engineer

Most Data Operations Engineer positions require at least a bachelor's degree in a related field such as computer science, information technology, or data science. Some positions may prefer or require a master's degree, especially for roles that involve more complex data analysis or machine learning tasks.

Helpful Certifications for a Data Operations Engineer

Certifications can enhance your resume and demonstrate your expertise. Some valuable certifications include:

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

These certifications can validate your skills in data management, cloud platforms, and data engineering, making you a more competitive candidate.

Experience Required for a Data Operations Engineer

Typically, employers look for candidates with 2-5 years of experience in data-related roles. Experience with data management, data warehousing, and familiarity with data processing tools and languages (such as SQL, Python, or R) is often required. Experience in a specific industry can also be beneficial, as it provides context for the data operations within that sector.

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