Salary for Executive-level / Director Analytics Engineer in United States during 2023

Salary details

The average executive-level / director Analytics Engineer salary lies between USD 170,000 and USD 221,000 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.

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: Nov. 17, 2024

Salary trend

Top 20 Job Tags for Executive-level / Director Analytics Engineer roles

The three most common job tag items assiciated with executive-level / director Analytics Engineer job listings are Engineering, Python 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:

Engineering | 9 jobs Python | 8 jobs SQL | 7 jobs Architecture | 4 jobs Data warehouse | 4 jobs R | 3 jobs Looker | 3 jobs Data Analytics | 3 jobs Consulting | 3 jobs BigQuery | 3 jobs Snowflake | 3 jobs Excel | 3 jobs Pipelines | 3 jobs APIs | 3 jobs Computer Science | 3 jobs Machine Learning | 2 jobs Spark | 2 jobs Redshift | 2 jobs Tableau | 2 jobs AWS | 2 jobs

Top 20 Job Perks/Benefits for Executive-level / Director Analytics Engineer roles

The three most common job benefits and perks assiciated with executive-level / director Analytics Engineer job listings are Startup environment, Health care and Career development. 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:

Startup environment | 7 jobs Health care | 6 jobs Career development | 6 jobs Parental leave | 3 jobs Flex hours | 3 jobs Flex vacation | 3 jobs Insurance | 3 jobs Salary bonus | 3 jobs 401(k) matching | 2 jobs Equity / stock options | 2 jobs Competitive pay | 2 jobs Team events | 2 jobs Medical leave | 1 jobs Home office stipend | 1 jobs Unlimited paid time off | 1 jobs

Salary Composition

In the United States, the salary composition for an Executive-level or Director Analytics Engineer in AI/ML/Data Science typically includes a combination of base salary, bonuses, and additional remuneration such as stock options or equity. The base salary often constitutes the largest portion, ranging from 60% to 80% of the total compensation package. Bonuses, which can be performance-based or tied to company success, usually account for 10% to 20%. Additional remuneration, such as stock options, equity, or other benefits, can make up the remaining 10% to 20%.

The composition can vary significantly 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 more substantial equity packages. In contrast, companies in the Midwest or South might offer lower base salaries but compensate with higher bonuses or other benefits. Larger companies or those in the tech industry often provide more comprehensive compensation packages compared to smaller firms or those in traditional industries.

Increasing Salary

To increase your salary further from this position, consider the following strategies:

• Skill Enhancement: Continuously update and expand your technical skills, especially in emerging AI/ML technologies and tools. This can make you more valuable to your current or potential employers.

• Leadership Development: Strengthen your leadership and management skills. Taking on more significant responsibilities or leading larger teams can justify a higher salary.

• Networking: Build a strong professional network within the industry. This can open up opportunities for higher-paying positions or roles in companies with more lucrative compensation packages.

• Industry Transition: Consider transitioning to industries that typically offer higher salaries for similar roles, such as finance or healthcare.

• Negotiation: Don’t hesitate to negotiate your salary during performance reviews or when offered a new position. Research industry standards and be prepared to present your case for a higher salary.

Educational Requirements

Most Executive-level or Director Analytics Engineer positions require at least a bachelor's degree in a relevant field such as Computer Science, Data Science, Statistics, or Engineering. However, a master's degree or Ph.D. is often preferred, especially for roles that demand a deep understanding of complex algorithms and data structures. Advanced degrees can also provide a competitive edge and may be necessary for positions in top-tier companies or highly specialized industries.

Helpful Certificates

While not always mandatory, certain certifications can enhance your qualifications and demonstrate your expertise. Some valuable certifications include:

• Certified Analytics Professional (CAP)
• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• Data Science Council of America (DASCA) Senior Data Scientist (SDS)

These certifications can validate your skills and knowledge, making you a more attractive candidate for higher-level positions.

Experience Requirements

Typically, a Director Analytics Engineer role requires significant experience, often 10+ years in the field of data science, machine learning, or analytics. This experience should include a mix of technical expertise, project management, and leadership roles. Experience in leading teams, managing large-scale projects, and developing strategic initiatives is highly valued. Additionally, experience in a specific industry can be beneficial, as it provides domain knowledge that can be crucial for certain roles.

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