Salary for Senior-level / Expert BI Engineer in United States during 2024

Salary details

The average senior-level / expert BI Engineer salary lies between USD 134,500 and USD 145,000 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. 10, 2024

Top 20 Job Tags for Senior-level / Expert BI Engineer roles

The three most common job tag items assiciated with senior-level / expert BI Engineer job listings are SQL, Engineering and Power BI. 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:

SQL | 89 jobs Engineering | 68 jobs Power BI | 64 jobs Business Intelligence | 59 jobs ETL | 50 jobs Computer Science | 46 jobs Python | 45 jobs Pipelines | 43 jobs AWS | 41 jobs Architecture | 41 jobs Azure | 40 jobs Snowflake | 40 jobs Tableau | 39 jobs Agile | 34 jobs Testing | 33 jobs GCP | 31 jobs Data pipelines | 29 jobs Big Data | 26 jobs Data Analytics | 26 jobs Data quality | 26 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert BI Engineer job listings are Career development, Flex hours and Health care. 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 | 67 jobs Flex hours | 41 jobs Health care | 37 jobs Flex vacation | 30 jobs Salary bonus | 30 jobs Medical leave | 29 jobs Competitive pay | 28 jobs Team events | 23 jobs Startup environment | 22 jobs Parental leave | 18 jobs Insurance | 18 jobs Equity / stock options | 17 jobs 401(k) matching | 15 jobs Wellness | 14 jobs Home office stipend | 9 jobs Conferences | 7 jobs Transparency | 6 jobs Gear | 3 jobs Relocation support | 3 jobs Unlimited paid time off | 3 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert BI Engineer in AI/ML/Data Science typically includes a combination of a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 70% to 85%. Bonuses can vary significantly depending on the company and industry, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can add a significant amount to the total compensation, especially if the company performs well.

Regional differences also play a role; for instance, salaries in tech hubs like San Francisco, New York, or Seattle tend to be higher due to the cost of living and competitive job markets. Industry-wise, tech companies, financial services, and healthcare often offer higher compensation packages compared to other sectors. Company size can also influence salary composition, with larger companies typically offering more comprehensive benefits and stock options.

Increasing Salary

To increase your salary further from a Senior-level BI Engineer position, consider the following strategies:

• Skill Enhancement: Continuously update and expand your technical skills, particularly in emerging AI/ML technologies and tools. Specializing in niche areas can make you more valuable.
• Leadership Roles: Transition into leadership or managerial roles, such as a BI Manager or Director of Data Science, which typically come with higher salaries.
• Industry Change: Moving to a higher-paying industry, such as finance or healthcare, can result in a salary increase.
• Networking and Visibility: Increase your professional visibility through networking, speaking at conferences, or publishing articles. This can lead to opportunities with higher compensation.
• Negotiation: Always negotiate your salary and benefits when offered a new position or during performance reviews.

Educational Requirements

Most Senior-level BI Engineer positions require at least a bachelor's degree in a related field such as Computer Science, Data Science, Statistics, or Information Systems. However, a master's degree or even a Ph.D. can be advantageous and sometimes preferred, especially for roles that require deep expertise in AI/ML. 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 your expertise:

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

These certifications can validate your skills and knowledge, making you more attractive to potential employers.

Experience Requirements

Typically, a Senior-level BI Engineer role requires at least 5 to 10 years of experience in business intelligence, data analysis, or a related field. Experience with data warehousing, ETL processes, and data visualization tools is often essential. Additionally, hands-on experience with AI/ML projects and familiarity with programming languages such as Python or R is highly valued.

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