Salary for Senior-level / Expert Analytics Engineer during 2022

Salary details

The average senior-level / expert Analytics Engineer salary lies between USD 110,000 and USD 184,700 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. 24, 2024

Salary trend

Top 20 Job Tags for Senior-level / Expert Analytics Engineer roles

The three most common job tag items assiciated with senior-level / expert Analytics Engineer job listings are SQL, Engineering and Python. 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:

SQL | 222 jobs Engineering | 218 jobs Python | 187 jobs Pipelines | 135 jobs Looker | 124 jobs Tableau | 104 jobs ETL | 101 jobs Snowflake | 101 jobs Data Analytics | 92 jobs Data pipelines | 87 jobs Airflow | 83 jobs Testing | 81 jobs AWS | 75 jobs BigQuery | 74 jobs Redshift | 70 jobs Git | 65 jobs Data warehouse | 65 jobs Business Intelligence | 63 jobs Computer Science | 63 jobs Data quality | 60 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Analytics Engineer roles

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

Career development | 156 jobs Startup environment | 107 jobs Health care | 100 jobs Flex vacation | 87 jobs Flex hours | 85 jobs Team events | 79 jobs Equity / stock options | 66 jobs Parental leave | 62 jobs Competitive pay | 54 jobs Home office stipend | 44 jobs Salary bonus | 41 jobs Medical leave | 38 jobs 401(k) matching | 35 jobs Unlimited paid time off | 34 jobs Insurance | 33 jobs Wellness | 30 jobs Fitness / gym | 17 jobs Conferences | 11 jobs Gear | 10 jobs Transparency | 8 jobs

Salary Composition

The salary for a Senior-level or Expert Analytics Engineer in AI/ML/Data Science 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 company-wide, usually make up 10-20% of the salary. Additional remuneration may include stock options, especially in tech companies, and other benefits like health insurance, retirement contributions, and professional development allowances. The composition can vary significantly depending on the region, industry, and company size. For instance, tech giants in Silicon Valley might offer substantial stock options, while companies in other regions might focus more on cash bonuses.

Increasing Salary

To increase your salary from a Senior-level position, consider the following strategies:

• Specialization: Develop expertise in a niche area of AI/ML, such as natural language processing or computer vision, which can command higher salaries.
• Leadership Roles: Transition into managerial or leadership roles, such as a team lead or director, which typically offer higher compensation.
• Consulting: Explore opportunities in consulting, where you can leverage your expertise across multiple projects and potentially earn more.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML to remain competitive and justify salary increases.

Educational Requirements

Most Senior-level Analytics Engineer positions require at least a bachelor's degree in a relevant field such as Computer Science, Data Science, Statistics, or Mathematics. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex problem-solving and advanced analytics. These advanced degrees provide a deeper understanding of machine learning algorithms, data structures, and statistical methods, which are crucial for high-level positions.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:

• Certified Analytics Professional (CAP)
• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate

These certifications validate your skills in specific platforms and tools, making you a more attractive candidate for senior roles.

Required Experience

Typically, a Senior-level Analytics Engineer is expected to have 5-10 years of experience in data science, machine learning, or a related field. This experience should include hands-on work with data analysis, model development, and deployment. Experience in leading projects or teams is also highly valued, as it demonstrates your ability to manage complex tasks and collaborate effectively with others.

Related salaries

Want to contribute?