Salary for Mid-level / Intermediate Analytics Engineer in United States during 2024

Salary details

The average mid-level / intermediate Analytics Engineer salary lies between USD 113,000 and USD 170,000 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: Jan. 19, 2025

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 2024 and the number of open jobs that where associated with them during that period:

SQL | 476 jobs Engineering | 414 jobs Python | 371 jobs Pipelines | 324 jobs dbt | 276 jobs ETL | 227 jobs Data Analytics | 222 jobs Data pipelines | 216 jobs Tableau | 209 jobs Data quality | 195 jobs Computer Science | 193 jobs Snowflake | 173 jobs Airflow | 169 jobs Looker | 168 jobs Business Intelligence | 153 jobs Testing | 151 jobs Architecture | 150 jobs AWS | 141 jobs Data visualization | 140 jobs Data warehouse | 133 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 2024 and the number of open jobs that where offering them during that period:

Career development | 332 jobs Health care | 218 jobs Flex hours | 158 jobs Startup environment | 158 jobs Equity / stock options | 149 jobs Competitive pay | 134 jobs Team events | 119 jobs Parental leave | 109 jobs Flex vacation | 102 jobs Insurance | 102 jobs Medical leave | 89 jobs Salary bonus | 74 jobs Home office stipend | 63 jobs 401(k) matching | 59 jobs Wellness | 53 jobs Unlimited paid time off | 50 jobs Fitness / gym | 46 jobs Conferences | 44 jobs Gear | 28 jobs Relocation support | 27 jobs

Salary Composition

The salary for a Mid-level/Intermediate 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 constitutes the majority 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 form a larger portion of the compensation package compared to other regions. In contrast, companies in the finance sector might offer higher base salaries with smaller bonuses. Company size also plays a role; larger companies often provide more comprehensive benefits and stock options, while smaller companies might offer higher base salaries to attract talent.

Increasing Salary

To increase your salary from a Mid-level/Intermediate Analytics Engineer position, consider the following steps:

• 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 data engineering can make you more valuable.
• Advanced Education: Pursuing a master's degree or Ph.D. in a relevant field can open up higher-paying opportunities.
• Leadership Roles: Transitioning into roles with more responsibility, such as a team lead or project manager, can lead to salary increases.
• Industry Change: Some industries, like finance or healthcare, may offer higher salaries for analytics roles compared to others.
• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or roles.

Educational Requirements

Most Mid-level/Intermediate Analytics Engineer positions require at least a bachelor's degree in a relevant field such as computer science, data science, statistics, or engineering. A master's degree can be advantageous and is often preferred by employers, especially for roles that require a deeper understanding of machine learning algorithms and data analysis techniques.

Helpful Certifications

While not always required, certain certifications can enhance your resume 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, deploy, and maintain machine learning solutions on AWS.
• Microsoft Certified: Azure Data Scientist Associate: Validates your skills in applying data science and machine learning to implement and run machine learning workloads on Azure.

Required Experience

Typically, a Mid-level/Intermediate Analytics Engineer is expected to have 3-5 years of experience in data analysis, data engineering, or a related field. Experience with data modeling, ETL processes, and proficiency in programming languages such as Python or R is often required. Familiarity with machine learning frameworks and tools like TensorFlow, PyTorch, or Scikit-learn is also beneficial.

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