Salary for Mid-level / Intermediate Analytics Engineer in United States during 2023

Salary details

The average mid-level / intermediate Analytics Engineer salary lies between USD 100,000 and USD 165,000 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: Dec. 22, 2024

Salary trend

Top 20 Job Tags for Mid-level / Intermediate Analytics Engineer roles

The three most common job tag items assiciated with mid-level / intermediate 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 | 77 jobs Engineering | 66 jobs Python | 60 jobs Pipelines | 44 jobs Data quality | 32 jobs dbt | 32 jobs Data pipelines | 31 jobs Snowflake | 31 jobs Tableau | 30 jobs ETL | 29 jobs Data Analytics | 29 jobs Airflow | 27 jobs Data warehouse | 26 jobs Looker | 25 jobs Architecture | 25 jobs Agile | 25 jobs Git | 25 jobs AWS | 24 jobs Computer Science | 24 jobs Power BI | 22 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Analytics Engineer roles

The three most common job benefits and perks assiciated with mid-level / intermediate 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 2023 and the number of open jobs that where offering them during that period:

Career development | 53 jobs Health care | 40 jobs Flex hours | 37 jobs Team events | 29 jobs Startup environment | 27 jobs Competitive pay | 24 jobs Flex vacation | 21 jobs Parental leave | 18 jobs Insurance | 18 jobs Salary bonus | 18 jobs Home office stipend | 17 jobs Equity / stock options | 15 jobs Wellness | 14 jobs Fitness / gym | 12 jobs Medical leave | 12 jobs Gear | 11 jobs 401(k) matching | 7 jobs Lunch / meals | 4 jobs Unlimited paid time off | 4 jobs Conferences | 3 jobs

Salary Composition for Mid-level Analytics Engineers

The salary for a Mid-level 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 might be more substantial compared to other areas. Additionally, larger companies often offer more comprehensive benefits packages, including health insurance, retirement plans, and other perks, which can add significant value to the overall compensation.

Steps to Increase Salary

To increase your salary from a Mid-level Analytics Engineer position, 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 relevant certifications can enhance your qualifications and open up higher-paying opportunities.
• Networking: Building a strong professional network can lead to new job opportunities and insights into industry trends.
• Leadership Roles: Transitioning into roles with more responsibility, such as a team lead or project manager, can lead to higher compensation.
• Industry Shift: Some industries, like finance or healthcare, may offer higher salaries for analytics roles compared to others.

Educational Requirements

Most Mid-level Analytics Engineer positions require at least a bachelor's degree in a related 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 roles that involve complex data modeling or machine learning.

Helpful Certifications

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

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• Google Professional Data Engineer: Focuses on designing, building, and operationalizing data processing systems.
• AWS Certified Machine Learning – Specialty: Demonstrates your ability to design, implement, and maintain machine learning solutions on AWS.
• Microsoft Certified: Azure Data Scientist Associate: Validates your skills in applying data science and machine learning techniques on Azure.

Experience Requirements

Typically, a Mid-level Analytics Engineer is expected to have 3-5 years of relevant experience. This experience should include hands-on work with data analysis, machine learning models, and data engineering tools. Experience in managing projects and collaborating with cross-functional teams is also valuable.

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