Salary for Senior-level / Expert Business Intelligence Engineer during 2024

Salary details

The average senior-level / expert Business Intelligence Engineer salary lies between USD 89,600 and USD 185,000 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: Dec. 22, 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 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:

Business Intelligence | 233 jobs SQL | 215 jobs Python | 149 jobs Tableau | 146 jobs Engineering | 145 jobs ETL | 112 jobs Statistics | 109 jobs Data visualization | 102 jobs Computer Science | 97 jobs AWS | 93 jobs Pipelines | 92 jobs Power BI | 85 jobs Redshift | 76 jobs Architecture | 72 jobs Finance | 69 jobs QuickSight | 69 jobs Data Mining | 68 jobs Security | 68 jobs Data analysis | 67 jobs Mathematics | 67 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, Health care and Equity / stock options. 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 | 154 jobs Health care | 113 jobs Equity / stock options | 85 jobs Parental leave | 77 jobs Medical leave | 68 jobs Insurance | 68 jobs Salary bonus | 61 jobs Team events | 54 jobs Competitive pay | 52 jobs Flex hours | 48 jobs Flex vacation | 48 jobs Wellness | 39 jobs Startup environment | 34 jobs Gear | 25 jobs 401(k) matching | 21 jobs Conferences | 18 jobs Flexible spending account | 16 jobs Signing bonus | 14 jobs Transparency | 5 jobs Unlimited paid time off | 5 jobs

Salary Composition

The salary for a Senior-level or Expert Business Intelligence Engineer in AI/ML/Data Science typically comprises several components. The fixed base salary is the largest portion, often accounting for 70-80% of the total compensation package. Bonuses, which can be performance-based or tied to company profits, usually make up 10-20% of the salary. Additional remuneration might include stock options, especially in tech companies, and other benefits like health insurance, retirement contributions, and paid time off. The composition can vary significantly depending on the region, industry, and company size. For instance, tech hubs like Silicon Valley or New York may offer higher base salaries and stock options, while smaller companies might provide more substantial bonuses to attract talent.

Increasing Salary

To increase your salary from this position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and tools. Specializing in niche areas like deep learning or natural language processing can make you more valuable.
• Leadership Roles: Transition into leadership or managerial roles, such as a Data Science Manager or Director of Analytics, which typically offer higher salaries.
• Industry Change: Moving to a higher-paying industry, such as finance or healthcare, where data-driven decision-making is critical, can lead to salary increases.
• Networking and Visibility: Attend industry conferences, publish papers, or speak at events to increase your visibility and attract offers from other companies.

Educational Requirements

Most Senior-level Business Intelligence Engineers in AI/ML/Data Science hold at least a bachelor's degree in a related field such as Computer Science, Data Science, Statistics, or Engineering. 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 also provide a competitive edge and potentially lead to higher salaries.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate expertise:

• Certified Analytics Professional (CAP)
• Microsoft Certified: Azure Data Scientist Associate
• Google Professional Data Engineer
• AWS Certified Machine Learning – Specialty

These certifications can validate your skills in specific tools and platforms, making you more attractive to potential employers.

Required Experience

Typically, a Senior-level Business Intelligence Engineer is expected to have 5-10 years of experience in data-related roles. This experience should include hands-on work with data analysis, machine learning models, and business intelligence tools. Experience in leading projects, mentoring junior team members, and collaborating with cross-functional teams is also highly valued.

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