Salary for Executive-level / Director Analytics Engineer during 2022

Salary details

The average executive-level / director Analytics Engineer salary lies between USD 150,000 and USD 200,000 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. 3, 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, SQL and Business Intelligence. Below you find a list of the 20 most occuring job tags in 2022 and the number of open jobs that where associated with them during that period:

Engineering | 6 jobs SQL | 5 jobs Business Intelligence | 5 jobs Python | 4 jobs AWS | 3 jobs Security | 3 jobs Privacy | 3 jobs Ruby | 2 jobs Machine Learning | 2 jobs Spark | 2 jobs Looker | 2 jobs Kubernetes | 2 jobs Data Analytics | 2 jobs Finance | 2 jobs BigQuery | 2 jobs SageMaker | 2 jobs GCP | 2 jobs Snowflake | 2 jobs Docker | 2 jobs Data governance | 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 Health care, Career development and 401(k) matching. Below you find a list of the 20 most occuring job perks or benefits in 2022 and the number of open jobs that where offering them during that period:

Health care | 5 jobs Career development | 5 jobs 401(k) matching | 4 jobs Equity / stock options | 4 jobs Flex vacation | 4 jobs Parental leave | 3 jobs Flex hours | 3 jobs Insurance | 3 jobs Unlimited paid time off | 3 jobs Startup environment | 2 jobs Lunch / meals | 1 jobs Wellness | 1 jobs Competitive pay | 1 jobs Team events | 1 jobs Medical leave | 1 jobs Fertility benefits | 1 jobs Paid sabbatical | 1 jobs

Salary Composition

The salary for an Executive-level or Director Analytics Engineer typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is often the largest component, accounting for 70-80% of the total compensation package. Performance bonuses can range from 10-20%, depending on the company's profitability and individual performance metrics. Additional remuneration, such as stock options, can vary significantly based on the company's size and industry. For instance, tech companies in Silicon Valley might offer substantial equity packages, while companies in other regions or industries might focus more on cash bonuses. Larger companies often have more structured bonus and equity programs, while smaller companies might offer more flexibility or higher equity stakes to attract top talent.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and tools. Specializing in niche areas like deep learning, natural language processing, or AI ethics can make you more valuable.
• Leadership Roles: Seek opportunities to lead larger teams or projects, demonstrating your ability to drive significant business impact.
• Networking: Build a strong professional network within the industry. Engaging with industry leaders and participating in conferences can open doors to higher-paying opportunities.
• Advanced Education: Pursuing further education, such as an MBA or a specialized master's degree, can position you for higher-level roles with increased compensation.
• Negotiation: When offered a new position or during performance reviews, negotiate for higher pay, emphasizing your contributions and market research on salary benchmarks.

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 systems. Advanced degrees can also provide a competitive edge in the job market and may be necessary for roles in research-intensive industries or academia.

Helpful Certifications

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 Machine Learning Engineer: Demonstrates proficiency in designing and building machine learning models on Google Cloud.
• AWS Certified Machine Learning – Specialty: Shows expertise in using AWS services to create, train, and deploy machine learning models.
• Microsoft Certified: Azure AI Engineer Associate: Highlights skills in using Azure AI services to build and integrate AI solutions.

Required Experience

Typically, candidates for this role need at least 8-10 years of experience in data science, analytics, or a related field. This experience should include a proven track record of managing teams, leading projects, and delivering data-driven solutions that impact business outcomes. Experience in a specific industry can also be beneficial, as it provides context and understanding of industry-specific challenges and opportunities.

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