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

Salary details

The average senior-level / expert Business Intelligence Engineer salary lies between USD 104,300 and USD 202,800 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. 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 the AI/ML/Data Science field typically comprises several components:

• Base Salary: This is the fixed annual amount and usually forms the largest portion of the total compensation. It can vary significantly based on the region, with tech hubs like San Francisco, New York, and Seattle offering higher base salaries compared to other areas.

• Bonus: Performance-based bonuses are common and can range from 10% to 20% of the base salary. These bonuses are often tied to individual performance, team success, or company profitability.

• Stock Options/Equity: Particularly in tech companies and startups, stock options or equity grants are a significant part of the compensation package. This can vary widely depending on the company's size and stage.

• Other Benefits: Additional remuneration may include health insurance, retirement contributions, and other perks like wellness programs, tuition reimbursement, and flexible working arrangements.

Increasing Salary

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

• Specialize Further: Developing expertise in a niche area of AI/ML, such as natural language processing or computer vision, can make you more valuable.

• Leadership Roles: Transitioning into managerial or leadership roles, such as a Director of Data Science or Chief Data Officer, can significantly increase your earning potential.

• Consulting or Freelancing: Offering your expertise as a consultant or freelancer can provide additional income streams and potentially higher hourly rates.

• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML to remain competitive and justify salary increases.

Educational Requirements

Most Senior-level Business Intelligence Engineers in AI/ML/Data Science roles 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.

Helpful Certifications

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

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.

• Microsoft Certified: Azure Data Scientist Associate: Demonstrates proficiency in using Azure's machine learning tools.

• AWS Certified Machine Learning – Specialty: Shows expertise in building, training, and deploying machine learning models on AWS.

• Google Professional Data Engineer: Certifies your ability to design, build, and operationalize data processing systems.

Required Experience

Typically, a Senior-level Business Intelligence Engineer is expected to have:

• 5-10 years of experience in data analysis, business intelligence, or a related field.
• Proven experience with data warehousing, ETL processes, and data visualization tools.
• Strong programming skills in languages such as Python, R, or SQL.
• Experience with machine learning frameworks and tools.

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