Data Management Lead Salary in United States during 2024
💰 The median Data Management Lead Salary in United States during 2024 is USD 116,600
✏️ This salary info is based on 12 individual salaries reported during 2024
Salary details
The average Data Management Lead salary lies between USD 102,000 and USD 144,300 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.
- Job title
- Data Management Lead
- Experience
- all levels
- Region
- United States
- Salary year
- 2024
- Sample size
- 12
- 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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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:Top 20 Job Tags for Data Management Lead roles
The three most common job tag items assiciated with Data Management Lead job listings are Data management, Research and Data governance. 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 | 97 jobs Research | 41 jobs Data governance | 38 jobs Data quality | 36 jobs Banking | 27 jobs GCP | 26 jobs Excel | 25 jobs Consulting | 24 jobs Engineering | 23 jobs SQL | 18 jobs DataOps | 18 jobs Computer Science | 17 jobs Security | 16 jobs Agile | 16 jobs CDISC | 16 jobs Finance | 15 jobs Biostatistics | 15 jobs Machine Learning | 13 jobs Classification | 13 jobs Privacy | 13 jobsTop 20 Job Perks/Benefits for Data Management Lead roles
The three most common job benefits and perks assiciated with Data Management Lead job listings are Career development, Health care and Team events. 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 | 45 jobs Health care | 28 jobs Team events | 27 jobs Competitive pay | 22 jobs Wellness | 18 jobs Flex hours | 16 jobs Equity / stock options | 11 jobs Parental leave | 11 jobs Startup environment | 11 jobs Insurance | 9 jobs Salary bonus | 8 jobs Travel | 7 jobs Medical leave | 6 jobs Home office stipend | 5 jobs Flex vacation | 4 jobs Relocation support | 3 jobs 401(k) matching | 2 jobs Fitness / gym | 2 jobs Transparency | 1 jobs Conferences | 1 jobsSalary Composition
In the United States, the salary composition for a Data Management Lead can vary significantly based on factors such as region, industry, and company size. Typically, the salary is divided into three main components: base salary, bonuses, and additional remuneration. The base salary is the fixed annual amount and usually constitutes the largest portion of the total compensation package. Bonuses, which can be performance-based or company-wide, often range from 10% to 20% of the base salary. Additional remuneration may include stock options, profit-sharing, or other incentives, which are more common in larger tech companies or startups. In regions with a high cost of living, such as the San Francisco Bay Area or New York City, salaries tend to be higher to compensate for living expenses. Similarly, industries like finance or technology may offer more competitive packages compared to non-profit or government sectors.
Increasing Salary
To increase your salary from the position of a Data Management Lead, consider the following strategies:
- Skill Enhancement: Continuously update your skills in emerging technologies and methodologies in AI/ML and data science. Specializing in niche areas like deep learning or big data analytics can make you more valuable.
- Advanced Education: Pursuing further education, such as a master's degree or Ph.D. in data science, computer science, or a related field, can open doors to higher-paying roles.
- Leadership Roles: Aim for roles with greater responsibility, such as a Director of Data Management or Chief Data Officer, which typically offer higher compensation.
- Networking: Engage with professional networks and industry conferences to increase your visibility and learn about higher-paying opportunities.
- Negotiation: When offered a new position or during performance reviews, negotiate for a higher salary based on your contributions and market research.
Educational Requirements
Most Data Management Lead positions require at least a bachelor's degree in a relevant field such as computer science, information technology, data science, or engineering. However, many employers prefer candidates with a master's degree or higher, especially for senior roles. A strong educational background provides a solid foundation in data management principles, programming, and analytical skills, which are crucial for the role.
Helpful Certifications
Certifications can enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications for a Data Management Lead include:
- Certified Data Management Professional (CDMP): Offered by DAMA International, this certification validates your knowledge and skills in data management.
- AWS Certified Big Data – Specialty: This certification is beneficial if you work with AWS technologies and big data solutions.
- Google Professional Data Engineer: This certification demonstrates your ability to design, build, and manage data processing systems on Google Cloud Platform.
- Microsoft Certified: Azure Data Engineer Associate: Useful for those working with Microsoft Azure, this certification covers data storage, processing, and security.
Experience Requirements
Typically, a Data Management Lead is expected to have 5 to 10 years of experience in data management, data analysis, or a related field. This experience should include hands-on work with data management tools, databases, and data governance frameworks. Leadership experience, such as managing a team or leading projects, is also highly valued, as the role often involves overseeing data management initiatives and coordinating with cross-functional teams.
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