Analytics Engineer Salary in United States during 2023

Salary details

The average Analytics Engineer salary lies between USD 125,000 and USD 187,000 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. 17, 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 for an Analytics Engineer

The salary for an Analytics Engineer in the United States 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, companies in other regions or smaller firms might offer smaller bonuses and fewer stock options. Industries such as finance and technology tend to offer higher compensation packages compared to sectors like education or non-profits.

Steps to Increase Salary

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

• Skill Enhancement: Continuously update your skills in the latest AI/ML technologies and tools. Specializing in high-demand areas like deep learning, natural language processing, or big data analytics can make you more valuable.
• Advanced Education: Pursuing a master's degree or Ph.D. in a related field can open up higher-paying opportunities.
• Networking: Building a strong professional network can lead to new job opportunities and insights into higher-paying roles.
• Leadership Roles: Transitioning into managerial or leadership positions can significantly increase your earning potential.
• Industry Switch: Moving to a higher-paying industry, such as finance or tech, can also result in a salary increase.

Educational Requirements

Most Analytics Engineer positions require at least a bachelor's degree in a relevant field such as computer science, data science, statistics, or engineering. A strong foundation in mathematics and programming is essential. Some employers may prefer candidates with a master's degree, especially for more advanced roles or in competitive industries.

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 Data Engineer
• Microsoft Certified: Azure Data Scientist Associate
• AWS Certified Machine Learning – Specialty
• SAS Certified Data Scientist

These certifications can help validate your skills and knowledge in specific tools and methodologies used in the field.

Experience Requirements

Typically, employers look for candidates with 2-5 years of experience in data analysis, data engineering, or a related field. Experience with data modeling, ETL processes, and working with large datasets is often required. Familiarity with programming languages such as Python, R, or SQL, and experience with data visualization tools like Tableau or Power BI, are also commonly expected.

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