Salary for Executive-level / Director Analytics Engineer during 2024

Salary details

The average executive-level / director Analytics Engineer salary lies between USD 180,000 and USD 247,500 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: Dec. 22, 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 typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The composition can vary significantly based on region, industry, and company size:

• Region: In the United States, tech hubs like Silicon Valley, New York, and Seattle often offer higher base salaries and more substantial equity packages compared to other regions. In Europe, cities like London and Berlin are known for competitive salaries, though they might offer less in terms of equity.

• Industry: Tech companies, especially those in AI and machine learning, tend to offer higher salaries and more lucrative stock options. Financial services and consulting firms also offer competitive packages, often with significant performance bonuses.

• Company Size: Larger companies may offer more stable base salaries and comprehensive benefits, while startups might provide lower base salaries but compensate with significant equity stakes and potential for rapid salary growth.

Increasing Salary Further

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

• Expand Your Skill Set: Stay updated with the latest AI/ML technologies and tools. Specializing in emerging areas like deep learning, natural language processing, or AI ethics can make you more valuable.

• Leadership and Management Skills: Enhance your leadership capabilities. Pursuing executive education programs or an MBA can prepare you for higher-level roles.

• Networking and Industry Engagement: Engage with industry conferences, seminars, and workshops. Building a strong professional network can open doors to higher-paying 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 roles 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 require deep technical expertise or research capabilities.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile:

• 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.

• Data Science Certifications: From platforms like Coursera, edX, or Udacity, these can provide specialized knowledge in data science and machine learning.

Required Experience

Typically, a minimum of 8-10 years of experience in data science, analytics, or a related field is required. This should include:

• Technical Expertise: Proficiency in programming languages like Python or R, and experience with data analysis and machine learning frameworks.

• Project Management: Experience in leading data-driven projects and managing cross-functional teams.

• Strategic Thinking: Ability to align data initiatives with business goals and drive strategic decision-making.

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