Salary for Mid-level / Intermediate Analytics Engineer during 2023

Salary details

The average mid-level / intermediate Analytics Engineer salary lies between USD 91,260 and USD 172,200 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. 17, 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

The salary for a Mid-level/Intermediate Analytics Engineer in AI/ML/Data Science typically comprises a fixed base salary, performance bonuses, and additional remuneration such as stock options or benefits. The fixed base salary is the largest component, often accounting for 70-80% of the total compensation package. Performance bonuses can vary significantly depending on the company and industry, ranging from 10-20% of the base salary. Additional remuneration, such as stock options, profit-sharing, or other benefits, can make up the remaining 5-10%.

Regional differences also play a significant role in salary composition. For instance, tech hubs like San Francisco or New York may offer higher base salaries and stock options, while regions with a lower cost of living might offer more modest packages. Industry-wise, tech companies and financial services often provide more lucrative bonuses and stock options compared to sectors like healthcare or education. Company size can also influence salary composition, with larger companies typically offering more comprehensive benefits and stock options.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in emerging technologies and tools relevant to AI/ML and data science. Specializing in niche 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 doors to higher-paying roles and leadership positions.

• Networking: Engage with industry professionals through conferences, workshops, and online platforms. Networking can lead to new job opportunities and insights into higher-paying roles.

• Certifications: Obtain relevant certifications that demonstrate your expertise and commitment to the field, which can justify a higher salary.

• Leadership Roles: Seek opportunities to lead projects or teams, as management experience can significantly boost your earning potential.

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. However, many employers prefer candidates with a master's degree, especially for roles involving complex data analysis and machine learning model development. A strong foundation in mathematics and statistics is essential, as is proficiency in programming languages like Python or R.

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: Demonstrates your skills in designing, building, and operationalizing data processing systems.
• AWS Certified Machine Learning – Specialty: Proves your ability to design, implement, and maintain machine learning solutions on AWS.
• Microsoft Certified: Azure Data Scientist Associate: Shows proficiency in applying data science and machine learning techniques on Azure.

Required Experience

Typically, a Mid-level/Intermediate Analytics Engineer role requires 3-5 years of experience in data analysis, machine learning, or a related field. Experience with data visualization tools, data warehousing solutions, and cloud platforms is often expected. Practical experience in deploying machine learning models and working with large datasets is highly valued.

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