Salary for Executive-level / Director Analytics Engineer in United States during 2024

Salary details

The average executive-level / director Analytics Engineer salary lies between USD 180,000 and USD 247,500 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 2024 and the number of open jobs that where associated with them during that period:

Engineering | 17 jobs Python | 13 jobs SQL | 13 jobs Redshift | 10 jobs Computer Science | 10 jobs Architecture | 9 jobs Machine Learning | 8 jobs Spark | 8 jobs Tableau | 8 jobs AWS | 8 jobs Pipelines | 8 jobs ETL | 7 jobs Business Intelligence | 7 jobs Data Analytics | 7 jobs Data governance | 7 jobs dbt | 7 jobs Big Data | 6 jobs Airflow | 6 jobs Security | 6 jobs Snowflake | 6 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 Career development, Health care and Parental leave. 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 Health care | 9 jobs Parental leave | 6 jobs Competitive pay | 6 jobs Equity / stock options | 5 jobs Flex hours | 5 jobs Startup environment | 5 jobs 401(k) matching | 4 jobs Flex vacation | 4 jobs Medical leave | 4 jobs Insurance | 4 jobs Salary bonus | 4 jobs Wellness | 3 jobs Unlimited paid time off | 2 jobs Gear | 1 jobs Team events | 1 jobs Home office stipend | 1 jobs Paid sabbatical | 1 jobs

Salary Composition

The salary for an Executive-level or Director Analytics Engineer in the AI/ML/Data Science field typically comprises several components. The fixed base salary is the largest portion, often accounting for 70-80% of the total compensation package. Bonuses, which can be performance-based or tied to company profits, usually make up 10-20% of the total salary. Additional remuneration may include stock options, especially in tech companies or startups, and other benefits such as health insurance, retirement contributions, and paid time off. 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 stock options, while companies in the finance sector might provide substantial bonuses.

Increasing Salary Further

To increase your salary beyond the median for this role, consider the following strategies:

• Expand Your Skill Set: Acquiring new skills in emerging technologies or methodologies can make you more valuable. Consider learning about advanced AI techniques, cloud computing, or big data analytics.
• Leadership and Management Training: Enhancing your leadership skills can prepare you for higher-level executive roles, which typically come with higher compensation.
• Networking and Industry Engagement: Building a strong professional network can open up opportunities for higher-paying positions. Attend industry conferences, join professional organizations, and engage in speaking opportunities.
• Performance and Results: Demonstrating a track record of successful projects and measurable results can position you for salary negotiations or promotions.

Educational Requirements

Most executive-level positions in AI/ML/Data Science require at least a bachelor's degree in a related 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 involve complex problem-solving and strategic decision-making. Advanced degrees can provide a deeper understanding of machine learning algorithms, data analysis techniques, and business strategy.

Helpful Certifications

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

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• Google Professional Machine Learning Engineer: Demonstrates proficiency in designing, building, and productionizing ML models.
• AWS Certified Machine Learning – Specialty: Shows expertise in using AWS services for machine learning solutions.
• Microsoft Certified: Azure AI Engineer Associate: Highlights skills in using Azure AI services.

Required Experience

Typically, a Director Analytics Engineer role requires 10-15 years of experience in data science, analytics, or a related field. This experience should include a mix of technical expertise, project management, and leadership roles. Experience in managing teams, developing data-driven strategies, and implementing large-scale analytics solutions is often essential.

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