Analytics Engineer Salary in 2023

Salary details

The average Analytics Engineer salary lies between USD 120,000 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. 10, 2024

Salary trend

Top 20 Job Tags for Analytics Engineer roles

The three most common job tag items assiciated with 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 | 549 jobs Engineering | 511 jobs Python | 438 jobs Pipelines | 321 jobs Snowflake | 262 jobs Looker | 244 jobs Tableau | 241 jobs ETL | 237 jobs Data Analytics | 227 jobs Airflow | 209 jobs Data pipelines | 209 jobs Data warehouse | 207 jobs Testing | 204 jobs dbt | 191 jobs Data quality | 188 jobs Architecture | 183 jobs Computer Science | 175 jobs AWS | 171 jobs Agile | 165 jobs BigQuery | 147 jobs

Top 20 Job Perks/Benefits for Analytics Engineer roles

The three most common job benefits and perks assiciated with 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 | 429 jobs Health care | 298 jobs Startup environment | 240 jobs Flex hours | 223 jobs Flex vacation | 202 jobs Team events | 196 jobs Equity / stock options | 188 jobs Salary bonus | 167 jobs Competitive pay | 157 jobs Insurance | 133 jobs Parental leave | 128 jobs Medical leave | 113 jobs Home office stipend | 85 jobs 401(k) matching | 74 jobs Fitness / gym | 74 jobs Wellness | 73 jobs Gear | 70 jobs Unlimited paid time off | 50 jobs Conferences | 34 jobs Relocation support | 26 jobs

Salary Composition

The salary for an Analytics Engineer in AI/ML/Data Science typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is the fixed component and usually forms the bulk of the total compensation package. Performance bonuses can vary significantly depending on the company's success and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration, like stock options, is more common in larger tech companies or startups and can significantly increase total compensation, especially if the company performs well. Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York tend to be higher due to the cost of living and competitive job market. Industry-wise, tech and finance sectors often offer higher compensation compared to others.

Steps to Increase Salary

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

• Skill Enhancement: Continuously upgrade your skills, especially in emerging technologies and tools relevant to AI/ML and data science.
• Advanced Education: Pursue advanced degrees or certifications that are highly regarded in the industry.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Performance Excellence: Consistently exceed performance expectations to position yourself for promotions or salary negotiations.
• Industry Transition: Consider moving to industries or companies known for higher compensation packages, such as tech giants or financial institutions.

Educational Requirements

Most Analytics Engineer roles 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. can be advantageous and sometimes necessary for more advanced positions or roles in research-intensive companies. A strong foundation in mathematics, statistics, and programming is essential, as these skills are critical for data analysis and model development.

Helpful Certifications

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

• Certified Analytics Professional (CAP)
• Google Professional Data Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure Data Scientist Associate
• Data Science Council of America (DASCA) Certifications

These certifications can validate your skills and knowledge, making you a more attractive candidate for higher-paying roles.

Required Experience

Typically, an Analytics Engineer position requires 3-5 years of experience in data analysis, engineering, or a related field. Experience with data modeling, ETL processes, and working with large datasets is often expected. Familiarity with programming languages such as Python, R, or SQL, and tools like Tableau, Power BI, or similar data visualization software is also crucial. Experience in a specific industry can be beneficial, as it provides domain knowledge that can be valuable in analytics roles.

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