Salary for Mid-level / Intermediate Data Operations Engineer in United States during 2024

Salary details

The average mid-level / intermediate Data Operations Engineer salary lies between USD 85,000 and USD 130,591 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 DataOps, SQL and Pipelines. 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 | 22 jobs SQL | 18 jobs Pipelines | 16 jobs Engineering | 15 jobs Python | 13 jobs Data pipelines | 12 jobs Data quality | 11 jobs Computer Science | 10 jobs ETL | 8 jobs AWS | 8 jobs Architecture | 8 jobs Big Data | 7 jobs Testing | 7 jobs Privacy | 7 jobs Spark | 6 jobs Agile | 6 jobs Machine Learning | 5 jobs GCP | 5 jobs Kafka | 4 jobs Tableau | 4 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 Career development, Health care and Competitive pay. 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 | 15 jobs Health care | 10 jobs Competitive pay | 6 jobs Equity / stock options | 5 jobs Wellness | 4 jobs Flex hours | 3 jobs Flex vacation | 3 jobs Startup environment | 3 jobs Team events | 3 jobs Medical leave | 3 jobs Transparency | 2 jobs Conferences | 2 jobs Salary bonus | 2 jobs Home office stipend | 2 jobs Parental leave | 1 jobs Travel | 1 jobs Fitness / gym | 1 jobs Insurance | 1 jobs

Salary Composition

The salary for a Mid-level 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 profitability and individual performance metrics. 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 based on several factors: - Region: Salaries in tech hubs like San Francisco, New York, or Seattle tend to be higher due to the cost of living and demand for tech talent. - Industry: Industries such as finance, healthcare, and technology often offer higher compensation compared to others. - Company Size: Larger companies may offer more comprehensive benefits and bonuses, while startups might offer equity as part of the compensation package.

Increasing 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, big data technologies, or cloud computing. Specializing in a niche area can make you more valuable. - Certifications: Obtain relevant certifications that demonstrate your expertise and commitment to the field. - Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends. - Advanced Education: Pursue a master's degree or specialized courses in data science or related fields. - Leadership Roles: Aim for roles with more responsibility, such as team lead or project manager, which often come with higher pay.

Educational Requirements

Most Mid-level Data Operations Engineer positions require at least a bachelor's degree in a relevant field such as computer science, data science, information technology, or engineering. 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

Certifications can enhance your resume and demonstrate your expertise. Some valuable certifications include: - Certified Data Management Professional (CDMP) - AWS Certified Big Data – Specialty - Google Professional Data Engineer - Microsoft Certified: Azure Data Engineer Associate - Cloudera Certified Data Engineer

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

Experience Requirements

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 data modeling 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 common.

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