Salary for Entry-level / Junior Data Manager during 2024

Salary details

The average entry-level / junior Data Manager salary lies between USD 45,000 and USD 95,000 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. 17, 2024

Top 20 Job Tags for Entry-level / Junior Data Manager roles

The three most common job tag items assiciated with entry-level / junior Data Manager job listings are Data management, Excel and Python. 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 | 21 jobs Excel | 18 jobs Python | 11 jobs SQL | 11 jobs Power BI | 10 jobs Engineering | 9 jobs R | 7 jobs Data governance | 6 jobs Data quality | 6 jobs Testing | 5 jobs Data analysis | 5 jobs RDBMS | 5 jobs Privacy | 5 jobs Tableau | 4 jobs Looker | 4 jobs Research | 4 jobs Business Intelligence | 4 jobs Security | 4 jobs APIs | 4 jobs Statistics | 3 jobs

Top 20 Job Perks/Benefits for Entry-level / Junior Data Manager roles

The three most common job benefits and perks assiciated with entry-level / junior Data Manager job listings are Career development, Flex hours and Health care. 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 | 16 jobs Flex hours | 11 jobs Health care | 8 jobs Competitive pay | 6 jobs Insurance | 6 jobs Team events | 4 jobs Flex vacation | 3 jobs Yoga | 3 jobs Salary bonus | 3 jobs 401(k) matching | 2 jobs Startup environment | 2 jobs Conferences | 2 jobs Flexible spending account | 2 jobs Relocation support | 1 jobs

Salary Composition

The salary for an entry-level or junior data manager in AI/ML/Data Science typically consists of a base salary, performance bonuses, and sometimes additional remuneration such as stock options or benefits. The composition can vary significantly based on region, industry, and company size:

• Region: In tech hubs like Silicon Valley or New York, the base salary might be higher due to the cost of living and demand for talent. In contrast, regions with a lower cost of living might offer a smaller base salary but could compensate with other benefits.
• Industry: Industries such as finance or healthcare may offer higher bonuses due to the critical nature of data management in these fields. Tech companies might provide stock options as part of the compensation package.
• Company Size: Larger companies often have more structured compensation packages, including comprehensive benefits and bonuses. Startups might offer lower base salaries but compensate with equity or performance-based bonuses.

Increasing Salary

To increase your salary from an entry-level position, consider the following steps:

• Skill Development: Continuously upgrade your skills in data analysis, machine learning, and data management tools. Proficiency in programming languages like Python or R, and familiarity with big data technologies, can make you more valuable.
• Advanced Education: Pursuing a master's degree or specialized courses in data science or AI can open up higher-paying opportunities.
• Networking: Engage with professional communities, attend industry conferences, and participate in workshops to expand your network and learn about new opportunities.
• Performance Excellence: Consistently exceed performance expectations and take on additional responsibilities to demonstrate your value to the organization.

Educational Requirements

Most entry-level data manager positions require at least a bachelor's degree in a related field such as computer science, data science, statistics, or information technology. Some employers may prefer candidates with a master's degree, especially for roles that involve more complex data analysis or management tasks.

Helpful Certificates

While not always mandatory, certain certifications can enhance your qualifications and make you more competitive:

• Certified Data Management Professional (CDMP): This certification demonstrates your expertise in data management principles and practices.
• Microsoft Certified: Azure Data Scientist Associate: Useful if you are working with Microsoft's cloud services.
• Google Professional Data Engineer: Beneficial for roles involving Google's cloud platform.
• AWS Certified Data Analytics – Specialty: Ideal for positions that require working with Amazon Web Services.

Experience Requirements

For an entry-level position, employers typically look for candidates with some practical experience, which can be gained through internships, co-op programs, or relevant project work during your studies. Experience with data analysis, database management, and familiarity with data visualization tools can be advantageous.

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