Salary for Senior-level / Expert Analytics Engineer in United States during 2024

Salary details

The average senior-level / expert Analytics Engineer salary lies between USD 130,000 and USD 190,800 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. 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

In the United States, the salary composition for a Senior-level or Expert Analytics Engineer in AI/ML/Data Science typically includes a combination of a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 70% to 85%. Bonuses can vary significantly depending on the company and industry, generally accounting for 10% to 20% of the total compensation. Additional remuneration, such as stock options, is more prevalent in larger tech companies and startups, potentially making up 5% to 15% of the total package. Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job markets.

Next Steps for Salary Increase

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

• Specialization: Develop expertise in a niche area within AI/ML, such as natural language processing, computer vision, or reinforcement learning, which can command higher salaries.
• Leadership Roles: Transition into managerial or leadership roles, such as a Director of Data Science or Chief Data Officer, which typically offer higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML through courses, workshops, and conferences.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Negotiation Skills: Enhance your negotiation skills to better advocate for higher compensation during job offers or performance reviews.

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 analytical techniques. Advanced degrees can provide a deeper understanding of machine learning algorithms, statistical models, and data analysis, which are crucial for high-level positions.

Helpful Certificates

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): 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 for building AI solutions.

Required Experience

Typically, a Senior-level Analytics Engineer is expected to have at least 5 to 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 a proven track record of solving complex business problems using data-driven approaches. Experience in leading projects or teams is also highly valued, as it demonstrates leadership and project management skills.

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