Data Operations Engineer Salary in United States during 2022

Salary details

The average Data Operations Engineer salary lies between USD 60,000 and USD 100,000 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. 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 Python, Engineering and SQL. Below you find a list of the 20 most occuring job tags in 2022 and the number of open jobs that where associated with them during that period:

Python | 17 jobs Engineering | 14 jobs SQL | 13 jobs DataOps | 11 jobs AWS | 8 jobs Research | 8 jobs Testing | 8 jobs Pipelines | 8 jobs Security | 7 jobs Architecture | 7 jobs Agile | 7 jobs APIs | 7 jobs NoSQL | 6 jobs Data pipelines | 6 jobs PostgreSQL | 6 jobs ETL | 5 jobs Hadoop | 5 jobs Redshift | 5 jobs Airflow | 5 jobs Statistics | 5 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, Startup environment and Equity / stock options. Below you find a list of the 20 most occuring job perks or benefits in 2022 and the number of open jobs that where offering them during that period:

Career development | 11 jobs Startup environment | 9 jobs Equity / stock options | 8 jobs Flex hours | 8 jobs Flex vacation | 7 jobs Health care | 6 jobs Parental leave | 5 jobs Competitive pay | 5 jobs Team events | 4 jobs Medical leave | 4 jobs 401(k) matching | 3 jobs Salary bonus | 3 jobs Lunch / meals | 1 jobs Wellness | 1 jobs Fitness / gym | 1 jobs Transparency | 1 jobs Insurance | 1 jobs Unlimited paid time off | 1 jobs Fertility benefits | 1 jobs

Salary Composition

The salary for a Data Operations Engineer in the United States typically consists of a base salary, performance 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. Performance bonuses can vary significantly depending on the company’s policy and individual performance, often ranging from 5% to 20% of the base salary. Additional remuneration might include stock options, especially in tech companies, and comprehensive benefits packages that cover health insurance, retirement plans, and other perks. The composition can vary by region, with tech hubs like Silicon Valley offering higher base salaries and stock options, while other regions might offer more competitive bonuses. Industry and company size also play a role; larger tech companies or those in high-demand industries may offer more lucrative packages compared to smaller firms or those in traditional sectors.

Steps to Increase Salary

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

• Skill Enhancement: Acquire advanced skills in AI/ML, data analytics, or cloud computing. Specializing in a niche area can make you more valuable.
• Certifications: Obtain relevant certifications that can validate your expertise and potentially lead to higher-paying roles.
• Networking: Engage with industry professionals through conferences, workshops, and online platforms to learn about new opportunities.
• Advanced Education: Pursue a master's degree or specialized courses in data science or related fields to enhance your qualifications.
• Performance Excellence: Consistently exceed performance expectations to position yourself for promotions or salary negotiations.

Educational Requirements

Most Data Operations Engineer positions require at least a bachelor's degree in computer science, information technology, data science, or a related field. Some employers may prefer candidates with a master's degree, especially for roles that involve complex data management or integration tasks. A strong foundation in mathematics, statistics, and programming is essential, as these skills are critical for handling data operations effectively.

Helpful Certifications

Certifications can be a valuable asset in demonstrating your expertise and commitment to the field. Some common and beneficial certifications include:

• Certified Data Management Professional (CDMP)
• AWS Certified Data Analytics – Specialty
• 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.

Experience Requirements

Typically, employers look for candidates with 2-5 years of experience in data operations, data engineering, or related roles. Experience with data management systems, ETL processes, and cloud platforms 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 highly valued.

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