Salary for Senior-level / Expert Analytics Engineer during 2024

Salary details

The average senior-level / expert Analytics Engineer salary lies between USD 130,000 and USD 190,000 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. 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 2024 and the number of open jobs that where associated with them during that period:

SQL | 834 jobs Engineering | 771 jobs Python | 690 jobs dbt | 525 jobs Pipelines | 478 jobs ETL | 390 jobs Snowflake | 383 jobs Looker | 382 jobs Tableau | 362 jobs Data quality | 345 jobs Data pipelines | 322 jobs Airflow | 318 jobs Testing | 309 jobs Data Analytics | 308 jobs AWS | 304 jobs Data warehouse | 301 jobs Computer Science | 297 jobs Architecture | 278 jobs Business Intelligence | 243 jobs BigQuery | 234 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, Health care and Flex hours. 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 | 632 jobs Health care | 404 jobs Flex hours | 377 jobs Startup environment | 324 jobs Equity / stock options | 322 jobs Flex vacation | 249 jobs Competitive pay | 246 jobs Team events | 219 jobs Parental leave | 216 jobs Salary bonus | 165 jobs Insurance | 145 jobs Medical leave | 137 jobs Wellness | 132 jobs 401(k) matching | 121 jobs Unlimited paid time off | 104 jobs Home office stipend | 95 jobs Fitness / gym | 77 jobs Gear | 54 jobs Transparency | 39 jobs Conferences | 37 jobs

Salary Composition

The salary for a Senior-level or Expert Analytics Engineer in AI/ML/Data Science typically comprises a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually forms the largest part of the total compensation package. Bonuses can be performance-based or company-wide and may vary significantly depending on the company's financial health and individual performance. Additional remuneration might include stock options, especially in tech companies or startups, and benefits like health insurance, retirement plans, and paid time off.

The composition can vary by 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 other regions might focus more on bonuses. Larger companies often provide more comprehensive benefits packages, whereas startups might offer more equity to compensate for lower base salaries.

Increasing Salary

To increase your salary from this 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 make you more valuable.
• Leadership Roles: Transition into leadership or managerial roles, such as a Director of Data Science or Chief Data Officer, which typically come with higher salaries.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML. This could involve taking advanced courses or attending workshops and conferences.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.

Educational Requirements

Most senior-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 research. Advanced degrees can provide a deeper understanding of machine learning algorithms, data analysis, and statistical modeling, which are crucial for this role.

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
• TensorFlow Developer Certificate

These certifications can validate your skills in specific tools and platforms, making you more competitive in the job market.

Required Experience

Typically, a senior-level analytics engineer is expected to have at least 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, as well as experience with programming languages like Python or R, and tools such as TensorFlow, PyTorch, or SQL. Experience in leading projects or teams is also highly valued, as it demonstrates your ability to manage complex tasks and collaborate effectively.

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