Data Lead Salary in United States during 2024
💰 The median Data Lead Salary in United States during 2024 is USD 146,620
✏️ This salary info is based on 50 individual salaries reported during 2024
Salary details
The average Data Lead salary lies between USD 122,000 and USD 180,000 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 Lead
- Experience
- all levels
- Region
- United States
- Salary year
- 2024
- Sample size
- 50
- 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:Salary trend
Top 20 Job Tags for Data Lead roles
The three most common job tag items assiciated with Data Lead job listings are Data management, Engineering 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 | 113 jobs Engineering | 85 jobs Data quality | 84 jobs SQL | 78 jobs Data governance | 77 jobs Architecture | 72 jobs Python | 62 jobs Research | 57 jobs Security | 55 jobs Data strategy | 51 jobs Agile | 51 jobs Computer Science | 49 jobs Finance | 48 jobs Testing | 46 jobs Data analysis | 46 jobs Power BI | 42 jobs ETL | 41 jobs Data Analytics | 41 jobs Excel | 41 jobs Machine Learning | 39 jobsTop 20 Job Perks/Benefits for Data Lead roles
The three most common job benefits and perks assiciated with Data Lead 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 | 141 jobs Health care | 81 jobs Flex hours | 69 jobs Competitive pay | 65 jobs Startup environment | 60 jobs Team events | 46 jobs Equity / stock options | 37 jobs Parental leave | 36 jobs Wellness | 32 jobs Insurance | 31 jobs Salary bonus | 28 jobs Medical leave | 26 jobs Flex vacation | 20 jobs Fitness / gym | 17 jobs Transparency | 13 jobs 401(k) matching | 10 jobs Home office stipend | 9 jobs Snacks / Drinks | 6 jobs Gear | 5 jobs Relocation support | 5 jobsSalary Composition for a Data Lead Role
The salary for a Data Lead in the United States typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. The base salary is the fixed component and usually forms the bulk of the total compensation package. Performance bonuses are often tied to individual, team, or company performance metrics and can vary significantly. Additional remuneration might include stock options, especially in tech companies or startups, and other benefits like health insurance, retirement plans, and paid time off.
The composition of these elements can vary depending on the region, industry, and company size. For instance, tech hubs like Silicon Valley or New York City might offer higher base salaries and stock options due to the high cost of living and competitive job market. In contrast, companies in the Midwest might offer a lower base salary but compensate with a more substantial bonus structure. Larger companies often provide more comprehensive benefits packages, while startups might offer more equity to attract talent.
Steps to Increase Salary from a Data Lead Position
To increase your salary from a Data Lead position, 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 can make you more valuable.
- Leadership Development: Develop your leadership and management skills to prepare for higher-level roles such as Director of Data Science or Chief Data Officer.
- Networking: Build a strong professional network within the industry. Attend conferences, webinars, and workshops to connect with industry leaders and peers.
- Performance Excellence: Consistently exceed performance expectations and take on challenging projects that demonstrate your value to the organization.
- Negotiation: Be prepared to negotiate your salary during performance reviews or when offered a new position. Research industry standards to make a compelling case.
Educational Requirements for a Data Lead
Most Data Lead positions require at least a bachelor's degree in a related field such as Computer Science, Statistics, Mathematics, or Engineering. However, a master's degree or Ph.D. is often preferred, especially for roles in research-intensive industries or companies. Advanced degrees provide a deeper understanding of complex data science concepts and methodologies, which can be crucial for leading a data team effectively.
Helpful Certifications for a Data Lead
While not always mandatory, certain certifications can enhance your credibility and demonstrate your expertise. Some valuable certifications include:
- Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
- Google Professional Data Engineer: Demonstrates proficiency in designing, building, and operationalizing data processing systems.
- AWS Certified Machine Learning – Specialty: Shows expertise in building, training, and deploying machine learning models on AWS.
- Microsoft Certified: Azure Data Scientist Associate: Validates your skills in applying data science techniques on Azure.
Experience Required for a Data Lead Role
Typically, a Data Lead position requires several years of experience in data science or a related field. This includes hands-on experience with data analysis, machine learning, and statistical modeling. Experience in leading projects and managing teams is also crucial, as the role involves overseeing data initiatives and guiding a team of data professionals. A track record of successful project delivery and the ability to translate business needs into data-driven solutions are highly valued.
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