Salary for Senior-level / Expert Business Intelligence Engineer during 2023

Salary details

The average senior-level / expert Business Intelligence Engineer salary lies between USD 104,300 and USD 192,000 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 Senior-level / Expert Business Intelligence Engineer roles

The three most common job tag items assiciated with senior-level / expert Business Intelligence Engineer job listings are Business Intelligence, SQL and Tableau. 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 | 145 jobs SQL | 139 jobs Tableau | 111 jobs Python | 108 jobs Engineering | 85 jobs ETL | 84 jobs Statistics | 68 jobs Computer Science | 67 jobs AWS | 63 jobs Pipelines | 63 jobs Data warehouse | 62 jobs Data visualization | 58 jobs Architecture | 56 jobs Redshift | 55 jobs Finance | 51 jobs Looker | 47 jobs Data Mining | 45 jobs Snowflake | 45 jobs Mathematics | 44 jobs QuickSight | 44 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Business Intelligence Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert 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 | 110 jobs Equity / stock options | 70 jobs Health care | 51 jobs Parental leave | 35 jobs Flex hours | 35 jobs Insurance | 32 jobs Salary bonus | 32 jobs Flex vacation | 30 jobs Wellness | 27 jobs Team events | 26 jobs Startup environment | 23 jobs Signing bonus | 21 jobs Medical leave | 19 jobs Competitive pay | 15 jobs Flexible spending account | 13 jobs Home office stipend | 6 jobs 401(k) matching | 4 jobs Conferences | 4 jobs Fertility benefits | 4 jobs Gear | 3 jobs

Salary Composition

The salary for a Senior-level or Expert Business Intelligence Engineer in AI/ML/Data Science typically comprises a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or profit-sharing. The composition can vary significantly depending on the region, industry, and company size. In tech hubs like Silicon Valley, the base salary might be higher, but bonuses and stock options can also form a substantial part of the total compensation package. In contrast, companies in regions with a lower cost of living might offer a lower base salary but compensate with other benefits. Industries such as finance or healthcare might offer higher bonuses due to the critical nature of data insights in these fields. Larger companies often provide more comprehensive benefits and stock options compared to smaller startups, which might offer higher base salaries to attract talent.

Increasing Salary

To increase your salary further from this position, consider pursuing leadership roles such as a Director of Business Intelligence or a Chief Data Officer. These roles typically come with higher compensation and more strategic responsibilities. Additionally, specializing in a niche area of AI/ML, such as natural language processing or computer vision, can make you more valuable. Networking within industry circles and attending conferences can also open up opportunities for higher-paying roles. Finally, consider negotiating your salary during performance reviews by demonstrating your impact on the company's bottom line through successful projects and initiatives.

Educational Requirements

Most Senior-level Business Intelligence Engineers in AI/ML/Data Science hold at least a bachelor's degree in computer science, data science, statistics, or a related field. However, a master's degree or Ph.D. is often preferred, especially for roles that require deep technical expertise or research capabilities. Advanced degrees can provide a competitive edge and are sometimes necessary for roles in academia or research-focused companies.

Helpful Certifications

Certifications can enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:

• Certified Business Intelligence Professional (CBIP)
• Microsoft Certified: Azure Data Scientist Associate
• Google Professional Data Engineer
• AWS Certified Machine Learning – Specialty
• SAS Certified Data Scientist

These certifications can validate your skills in specific tools and platforms, making you more attractive to employers looking for expertise in those areas.

Required Experience

Typically, a Senior-level Business Intelligence Engineer is expected to have at least 5-10 years of experience in data analysis, business intelligence, or a related field. This experience should include a strong track record of delivering data-driven insights and solutions. Experience with data warehousing, ETL processes, and data visualization tools is often required. Additionally, experience in leading projects or teams can be beneficial for demonstrating leadership capabilities.

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