Salary for Senior-level / Expert Analytics Engineer during 2023

Salary details

The average senior-level / expert Analytics Engineer salary lies between USD 128,000 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: Dec. 22, 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 2023 and the number of open jobs that where associated with them during that period:

SQL | 347 jobs Engineering | 336 jobs Python | 264 jobs Pipelines | 212 jobs Looker | 186 jobs Snowflake | 174 jobs Tableau | 167 jobs ETL | 149 jobs Data warehouse | 147 jobs Testing | 145 jobs Data pipelines | 137 jobs Airflow | 129 jobs Data Analytics | 129 jobs Architecture | 128 jobs dbt | 116 jobs Data quality | 114 jobs Computer Science | 108 jobs Redshift | 105 jobs AWS | 102 jobs BigQuery | 99 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 Startup environment. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:

Career development | 285 jobs Health care | 206 jobs Startup environment | 161 jobs Flex vacation | 156 jobs Equity / stock options | 144 jobs Flex hours | 141 jobs Team events | 121 jobs Salary bonus | 121 jobs Competitive pay | 103 jobs Insurance | 91 jobs Medical leave | 87 jobs Parental leave | 86 jobs 401(k) matching | 61 jobs Wellness | 52 jobs Fitness / gym | 49 jobs Gear | 48 jobs Home office stipend | 47 jobs Unlimited paid time off | 33 jobs Conferences | 26 jobs Fertility benefits | 18 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 vary significantly depending on the company's performance, individual performance, and industry standards. In tech-heavy regions like Silicon Valley, bonuses and stock options can be substantial, often making up a significant portion of the total compensation. In contrast, in regions with a lower cost of living, the base salary might be more dominant. Larger companies or those in high-growth industries like tech or finance often offer more competitive packages, including generous bonuses and stock options, compared to smaller companies or those in more traditional industries.

Increasing Salary

To increase your salary from a Senior-level position, consider pursuing leadership roles such as a Director of Analytics or Chief Data Officer. These roles often come with higher compensation and more strategic responsibilities. Additionally, specializing in high-demand areas like machine learning engineering, AI ethics, or data strategy can make you more valuable. Networking within industry circles, attending conferences, and publishing in reputable journals can also enhance your visibility and reputation, potentially leading to higher-paying opportunities. Negotiating your salary based on market research and your contributions to the company can also be effective.

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 Engineering. 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, statistical methods, and data management, which are crucial for high-level analytics roles.

Helpful Certifications

While not always mandatory, certain certifications can enhance your qualifications and demonstrate your expertise. Certifications such as Certified Analytics Professional (CAP), Google Professional Machine Learning Engineer, or AWS Certified Machine Learning can be beneficial. These certifications validate your skills in specific tools and methodologies, making you more attractive to potential employers. Additionally, specialized courses in data science and machine learning from platforms like Coursera, edX, or Udacity can also be advantageous.

Required Experience

Typically, a Senior-level Analytics Engineer is expected to have at least 5-10 years of experience in data science, analytics, or a related field. This experience should include hands-on work with data analysis, machine learning models, and data engineering. Experience in leading projects, mentoring junior team members, and collaborating with cross-functional teams is also highly valued. Demonstrated success in delivering data-driven insights and solutions that have a tangible impact on business outcomes is crucial.

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