Data Operations Analyst Salary in 2023

Salary details

The average Data Operations Analyst salary lies between USD 65,100 and USD 144,000 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. 10, 2024

Salary trend

Top 20 Job Tags for Data Operations Analyst roles

The three most common job tag items assiciated with Data Operations Analyst job listings are DataOps, Data quality 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 | 40 jobs Data quality | 28 jobs SQL | 26 jobs Excel | 24 jobs Salesforce | 16 jobs Python | 13 jobs Engineering | 13 jobs Data analysis | 13 jobs FinTech | 12 jobs Data management | 10 jobs Business Intelligence | 8 jobs Testing | 8 jobs Jira | 8 jobs Computer Science | 8 jobs Privacy | 8 jobs R | 7 jobs Data governance | 7 jobs Finance | 6 jobs Power BI | 6 jobs Confluence | 6 jobs

Top 20 Job Perks/Benefits for Data Operations Analyst roles

The three most common job benefits and perks assiciated with Data Operations Analyst job listings are Career development, Health care and Startup environment. 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 | 20 jobs Health care | 16 jobs Startup environment | 12 jobs Flex hours | 11 jobs Salary bonus | 9 jobs Gear | 8 jobs Equity / stock options | 4 jobs Team events | 4 jobs Home office stipend | 4 jobs Flex vacation | 3 jobs Medical leave | 3 jobs Insurance | 3 jobs Parental leave | 2 jobs Wellness | 2 jobs Fitness / gym | 2 jobs Transparency | 2 jobs Competitive pay | 1 jobs Unlimited paid time off | 1 jobs

Salary Composition

The salary for a Data Operations Analyst typically comprises a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or benefits. The fixed base salary often constitutes the majority of the total compensation package, usually around 70-80%. Bonuses can vary significantly depending on the company and industry, ranging from 5-20% of the base salary. Additional remuneration, such as stock options, profit-sharing, or comprehensive benefits packages, can make up the remaining 5-10%.

Regional differences also play a significant role; for instance, salaries in tech hubs like San Francisco or New York tend to be higher due to the cost of living and demand for skilled professionals. Industry-wise, tech companies and financial services often offer more competitive compensation packages compared to other sectors. Larger companies may provide more substantial bonuses and stock options, while smaller companies might offer more flexible work arrangements or other non-monetary benefits.

Increasing Salary

To increase your salary from a Data Operations Analyst position, consider the following steps:

• Skill Enhancement: Continuously upgrade your skills in data analysis, machine learning, and data engineering. Proficiency in programming languages like Python or R, and tools like SQL, Hadoop, or Spark, can make you more valuable.

• Advanced Education: Pursuing a master's degree or specialized certifications in data science or machine learning can open up higher-paying roles.

• Networking: Engage with industry professionals through conferences, workshops, and online platforms like LinkedIn. Networking can lead to new opportunities and insights into higher-paying roles.

• Performance and Negotiation: Consistently demonstrate high performance and take on challenging projects. When the time is right, negotiate for a raise or promotion based on your contributions and market research.

• Explore New Opportunities: Sometimes, the best way to increase your salary is to explore opportunities with other companies that may offer better compensation packages.

Educational Requirements

Most Data Operations Analyst positions require at least a bachelor's degree in a related field such as computer science, information technology, statistics, or mathematics. Some roles may prefer candidates with a master's degree, especially in data science or business analytics. A strong foundation in quantitative analysis and data management is essential.

Helpful Certifications

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

• Certified Analytics Professional (CAP)
• Microsoft Certified: Azure Data Scientist Associate
• Google Professional Data Engineer
• AWS Certified Data Analytics – Specialty
• SAS Certified Data Scientist

These certifications can help you stand out in the job market and may lead to better job opportunities and salary prospects.

Experience Requirements

Typically, a Data Operations Analyst role requires 2-5 years of experience in data analysis, data management, or a related field. Experience with data visualization tools, statistical analysis, and data warehousing is often expected. Familiarity with industry-specific data and business processes can also be advantageous.

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