Salary for Mid-level / Intermediate Data Operations Engineer in United States during 2022

Salary details

The average mid-level / intermediate 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: Dec. 22, 2024

Salary trend

Top 20 Job Tags for Mid-level / Intermediate Data Operations Engineer roles

The three most common job tag items assiciated with mid-level / intermediate Data Operations Engineer job listings are Python, SQL and Airflow. 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 | 4 jobs SQL | 4 jobs Airflow | 4 jobs Engineering | 4 jobs Testing | 4 jobs Architecture | 3 jobs Statistics | 3 jobs Mathematics | 3 jobs STEM | 3 jobs DataOps | 3 jobs Privacy | 3 jobs Machine Learning | 1 jobs ETL | 1 jobs Research | 1 jobs Consulting | 1 jobs Banking | 1 jobs Finance | 1 jobs Data pipelines | 1 jobs FinTech | 1 jobs Data strategy | 1 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Data Operations Engineer roles

The three most common job benefits and perks assiciated with mid-level / intermediate Data Operations Engineer job listings are Equity / stock options, Flex hours and Flex vacation. 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:

Equity / stock options | 4 jobs Flex hours | 4 jobs Flex vacation | 4 jobs Career development | 4 jobs Competitive pay | 4 jobs Parental leave | 3 jobs Health care | 3 jobs Medical leave | 3 jobs Salary bonus | 3 jobs Startup environment | 1 jobs Team events | 1 jobs

Salary Composition

The salary for a Mid-level Data Operations Engineer in the United States typically comprises a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually forms the bulk of the total compensation package. Bonuses can vary significantly depending on the company's performance, individual performance, and industry standards. In tech-heavy regions like Silicon Valley, bonuses and stock options might be more prevalent, whereas in other regions, the base salary might be more emphasized. Larger companies often offer more comprehensive benefits packages, including health insurance, retirement plans, and sometimes educational reimbursements, which can add significant value to the overall compensation.

Steps to Increase Salary

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

• Skill Enhancement: Acquire advanced skills in AI/ML, data engineering, or cloud computing. Specializing in a niche area can make you more valuable.
• Certifications: Obtain relevant certifications that are recognized in the industry.
• Networking: Engage with industry professionals through conferences, meetups, and online platforms to learn about new opportunities.
• Performance Excellence: Consistently exceed performance expectations and take on leadership roles in projects.
• Advanced Education: Consider pursuing a master's degree or specialized courses in data science or related fields.

Educational Requirements

Most Mid-level Data Operations Engineer positions require at least a bachelor's degree in computer science, data science, information technology, or a related field. Some employers may prefer candidates with a master's degree, especially for roles that involve complex data analysis or machine learning tasks. A strong foundation in mathematics and statistics is also beneficial.

Helpful Certifications

Several certifications can enhance your qualifications for a Data Operations Engineer role:

• 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 demonstrate your expertise in data management and cloud platforms, which are crucial for data operations roles.

Required Experience

Typically, a Mid-level Data Operations Engineer is expected to have 3-5 years of experience in data engineering, data analysis, or a related field. Experience with data warehousing, ETL processes, and cloud platforms is often required. Familiarity with programming languages such as Python, SQL, and tools like Apache Spark or Hadoop is also common.

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