Salary for Mid-level / Intermediate Analytics Engineer in United States during 2022

Salary details

The average mid-level / intermediate Analytics Engineer salary lies between USD 85,000 and USD 122,500 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. 24, 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, Python and Engineering. Below you find a list of the 20 most occuring job tags in 2022 and the number of open jobs that where associated with them during that period:

SQL | 34 jobs Python | 26 jobs Engineering | 22 jobs Tableau | 19 jobs ETL | 18 jobs Snowflake | 18 jobs Power BI | 15 jobs Data Analytics | 14 jobs BigQuery | 14 jobs Pipelines | 14 jobs AWS | 13 jobs Testing | 13 jobs Agile | 13 jobs Redshift | 11 jobs Data pipelines | 11 jobs Azure | 11 jobs APIs | 11 jobs Looker | 10 jobs Airflow | 10 jobs GitHub | 10 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, Startup environment and Health care. Below you find a list of the 20 most occuring job perks or benefits in 2022 and the number of open jobs that where offering them during that period:

Career development | 25 jobs Startup environment | 19 jobs Health care | 17 jobs Competitive pay | 17 jobs Flex hours | 14 jobs Team events | 12 jobs Flex vacation | 10 jobs Equity / stock options | 9 jobs Insurance | 8 jobs Parental leave | 7 jobs 401(k) matching | 6 jobs Travel | 6 jobs Yoga | 6 jobs Medical leave | 6 jobs Salary bonus | 6 jobs Gear | 2 jobs Fitness / gym | 2 jobs Lunch / meals | 1 jobs Wellness | 1 jobs Flexible spending account | 1 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 forms the bulk of the total compensation package. Bonuses can vary significantly depending on the company's performance, individual performance, and industry standards. For instance, tech companies might offer higher bonuses compared to non-tech industries. Additional remuneration might include stock options, especially in tech startups or large tech firms, and benefits like health insurance, retirement plans, and paid time off. The composition can also vary by region, with tech hubs like San Francisco or New York offering higher base salaries and bonuses compared to other regions.

Increasing Salary

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

• Skill Enhancement: Continuously upgrade your skills in emerging technologies and tools relevant to AI/ML and data science. Proficiency in advanced machine learning algorithms, big data technologies, and cloud platforms can make you more valuable.
• Advanced Education: Pursuing a master's degree or specialized courses in data science, machine learning, or related fields can enhance your qualifications.
• Networking: Engage with professional networks and communities. Attending conferences, webinars, and meetups can open up new opportunities and provide insights into industry trends.
• Leadership Roles: Seek opportunities to lead projects or teams, which can position you for roles with greater responsibility and higher pay.
• Switching Companies: Sometimes, moving to a different company, especially in a high-demand region or industry, can result in a significant salary increase.

Educational Requirements

Most mid-level analytics engineering positions require at least a bachelor's degree in a relevant field such as computer science, data science, statistics, or engineering. Some employers may prefer candidates with a master's degree, especially for roles that involve complex data analysis or machine learning tasks. A strong foundation in mathematics and statistics is often essential, along with programming skills in languages like Python or R.

Helpful Certificates

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 expertise in building, training, tuning, and deploying machine learning models on AWS.
• Microsoft Certified: Azure Data Scientist Associate: Validates your skills in applying data science and machine learning techniques on Azure.

Required Experience

Typically, a mid-level 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 working with large datasets is often required. Familiarity with data visualization tools and experience in deploying machine learning models can also be advantageous.

Related salaries

Want to contribute?