Business Intelligence Engineer Salary in United States during 2023

Salary details

The average Business Intelligence Engineer salary lies between USD 104,300 and USD 185,900 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 Business Intelligence Engineer roles

The three most common job tag items assiciated with Business Intelligence Engineer job listings are Business Intelligence, SQL 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:

Business Intelligence | 199 jobs SQL | 186 jobs Python | 148 jobs Tableau | 148 jobs ETL | 121 jobs Engineering | 119 jobs Statistics | 92 jobs Computer Science | 89 jobs Pipelines | 88 jobs Data visualization | 87 jobs AWS | 85 jobs Data warehouse | 75 jobs Architecture | 72 jobs Redshift | 71 jobs R | 65 jobs Power BI | 65 jobs Finance | 61 jobs Looker | 60 jobs QuickSight | 59 jobs Mathematics | 55 jobs

Top 20 Job Perks/Benefits for Business Intelligence Engineer roles

The three most common job benefits and perks assiciated with Business Intelligence Engineer job listings are Career development, Equity / stock options and Health care. 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 | 148 jobs Equity / stock options | 83 jobs Health care | 67 jobs Flex hours | 52 jobs Parental leave | 46 jobs Flex vacation | 43 jobs Insurance | 40 jobs Salary bonus | 40 jobs Startup environment | 38 jobs Team events | 35 jobs Wellness | 32 jobs Medical leave | 27 jobs Competitive pay | 23 jobs Signing bonus | 23 jobs Flexible spending account | 17 jobs Home office stipend | 12 jobs 401(k) matching | 7 jobs Gear | 6 jobs Conferences | 6 jobs Fitness / gym | 4 jobs

Salary Composition

The salary for a Business Intelligence Engineer in the AI/ML/Data Science field typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. The base salary is the fixed component and usually forms the largest part of the total compensation package. Performance bonuses are often tied to individual, team, or company performance metrics and can vary significantly. Additional remuneration might include stock options, especially in tech companies, or profit-sharing plans, which are more common in larger corporations.

The composition of these elements can vary based on several factors:

• Region: Salaries in tech hubs like Silicon Valley or New York City tend to be higher due to the cost of living and demand for talent.
• Industry: Industries such as finance and technology often offer higher compensation packages compared to sectors like education or non-profits.
• Company Size: Larger companies may offer more comprehensive benefits and bonuses, while startups might provide equity options as part of the compensation package.

Increasing Salary

To increase your salary from the position of a Business Intelligence Engineer, consider the following steps:

• Skill Enhancement: Continuously update your skills in emerging technologies and tools relevant to AI/ML and data science. Proficiency in advanced analytics, machine learning algorithms, and data visualization tools can make you more valuable.
• Advanced Education: Pursuing a master's degree or specialized certifications in data science or AI can enhance your qualifications and open up higher-paying opportunities.
• Leadership Roles: Transitioning into managerial or leadership roles can significantly increase your earning potential. This might involve leading a team of data scientists or managing larger projects.
• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or roles. Attend industry conferences, join professional groups, and engage in online forums.

Educational Requirements

Most Business Intelligence Engineer roles require at least a bachelor's degree in a related field such as computer science, information technology, data science, or business analytics. However, a master's degree can be advantageous and is often preferred by employers, especially for roles that involve complex data analysis and strategic decision-making.

Helpful Certifications

Certifications can bolster your credentials and demonstrate expertise in specific areas. Some valuable certifications include:

• Certified Business Intelligence Professional (CBIP): Focuses on data management and analytics.
• Microsoft Certified: Azure Data Scientist Associate: Validates skills in using Azure for data science solutions.
• Google Professional Data Engineer: Demonstrates proficiency in designing and building data processing systems on Google Cloud.
• AWS Certified Data Analytics – Specialty: Focuses on using AWS services for data analytics.

Experience Requirements

Typically, employers look for candidates with 3-5 years of experience in data analysis, business intelligence, or a related field. Experience with data warehousing, ETL processes, and data visualization tools like Tableau or Power BI is often required. Familiarity with programming languages such as SQL, Python, or R is also essential.

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