Data Management Analyst Salary in 2024
💰 The median Data Management Analyst Salary in 2024 is USD 91,062
✏️ This salary info is based on 96 individual salaries reported during 2024
Salary details
The average Data Management Analyst salary lies between USD 69,960 and USD 124,935 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.
- Job title
- Data Management Analyst
- Experience
- all levels
- Region
- global/worldwide
- Salary year
- 2024
- Sample size
- 96
- Top 10%
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- Top 25%
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- Median
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- Bottom 25%
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- Bottom 10%
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All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.
Last updated:Top 20 Job Tags for Data Management Analyst roles
The three most common job tag items assiciated with Data Management Analyst job listings are Data management, Excel and Data quality. 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:
Data management | 208 jobs Excel | 96 jobs Data quality | 86 jobs Research | 69 jobs SQL | 66 jobs Security | 62 jobs Data governance | 59 jobs Engineering | 49 jobs Finance | 49 jobs Data analysis | 46 jobs Computer Science | 38 jobs Privacy | 34 jobs Tableau | 31 jobs Testing | 28 jobs Statistics | 28 jobs Python | 26 jobs Data Analytics | 26 jobs Power BI | 26 jobs R | 23 jobs Classification | 22 jobsTop 20 Job Perks/Benefits for Data Management Analyst roles
The three most common job benefits and perks assiciated with Data Management Analyst 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 | 105 jobs Health care | 81 jobs Flex hours | 59 jobs Medical leave | 44 jobs Insurance | 44 jobs Flex vacation | 40 jobs Competitive pay | 40 jobs Salary bonus | 39 jobs Parental leave | 34 jobs Team events | 34 jobs Equity / stock options | 31 jobs Startup environment | 31 jobs Wellness | 29 jobs 401(k) matching | 28 jobs Relocation support | 9 jobs Home office stipend | 6 jobs Fitness / gym | 5 jobs Conferences | 5 jobs Flexible spending account | 5 jobs Unlimited paid time off | 5 jobsSalary Composition for a Data Management Analyst
The salary composition for a Data Management Analyst can vary significantly based on factors such as region, industry, and company size. Typically, the salary is composed of a fixed base salary, which forms the bulk of the compensation package. In the United States, for instance, the base salary might account for 70-85% of the total compensation. Bonuses, which can be performance-based or company-wide, often make up 10-20% of the total salary. Additional remuneration might include stock options, especially in tech companies, and benefits such as health insurance, retirement contributions, and paid time off. 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. Similarly, larger companies or those in the tech industry might offer more competitive bonuses and stock options compared to smaller firms or those in traditional industries.
Steps to Increase Salary from a Data Management Analyst Position
To increase your salary from a Data Management Analyst position, consider the following strategies:
- Skill Enhancement: Continuously update your skills in data analysis, machine learning, and data management tools. Proficiency in programming languages like Python or R, and experience with data visualization tools like Tableau or Power BI, can make you more valuable.
- Advanced Education: Pursuing a master's degree or specialized courses in data science or machine learning can open up higher-paying opportunities.
- Networking: Engage with industry professionals through conferences, workshops, and online platforms like LinkedIn. Networking can lead to new job opportunities and insights into salary trends.
- Certifications: Obtain relevant certifications that can validate your skills and make you stand out to employers.
- Performance and Negotiation: Consistently perform well in your current role and be prepared to negotiate your salary during performance reviews or when offered a new position.
Educational Requirements for a Data Management Analyst
Most Data Management Analyst positions require at least a bachelor's degree in a related field such as computer science, information technology, statistics, or mathematics. Some employers may prefer candidates with a master's degree, especially for roles that involve complex data analysis or machine learning tasks. Coursework in database management, data analysis, and programming is often essential. Additionally, familiarity with business concepts can be beneficial, as data management often involves understanding business needs and translating them into data solutions.
Helpful Certifications for a Data Management Analyst
Several certifications can enhance your qualifications as a Data Management Analyst:
- Certified Data Management Professional (CDMP): Offered by DAMA International, this certification validates your expertise in data management.
- Microsoft Certified: Azure Data Scientist Associate: This certification demonstrates your ability to apply data science techniques using Azure.
- Google Professional Data Engineer: This certification shows your proficiency in designing and managing data processing systems on Google Cloud.
- SAS Certified Data Scientist: This certification covers data manipulation, predictive modeling, and machine learning using SAS tools.
Experience Required for a Data Management Analyst
Typically, employers look for candidates with 2-5 years of experience in data management, data analysis, or a related field. Experience with data management systems, data warehousing, and data governance is often required. Familiarity with data modeling, ETL processes, and data quality assurance can also be important. For more senior roles, additional experience in project management or team leadership might be necessary.
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