Salary for Mid-level / Intermediate Business Intelligence Engineer in United States during 2023

Salary details

The average mid-level / intermediate Business Intelligence Engineer salary lies between USD 79,600 and USD 185,000 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: Dec. 22, 2024

Salary trend

Top 20 Job Tags for Mid-level / Intermediate Business Intelligence Engineer roles

The three most common job tag items assiciated with mid-level / intermediate 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 | 23 jobs SQL | 20 jobs Python | 16 jobs Engineering | 16 jobs ETL | 14 jobs Tableau | 14 jobs Data visualization | 14 jobs Pipelines | 13 jobs Statistics | 12 jobs Power BI | 11 jobs Architecture | 10 jobs Redshift | 9 jobs R | 8 jobs Data pipelines | 8 jobs Computer Science | 8 jobs Data quality | 8 jobs AWS | 7 jobs Data Analytics | 7 jobs CX | 7 jobs Agile | 7 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Business Intelligence Engineer roles

The three most common job benefits and perks assiciated with mid-level / intermediate Business Intelligence Engineer job listings are Career development, Health care and Flex hours. 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 | 15 jobs Health care | 10 jobs Flex hours | 8 jobs Flex vacation | 6 jobs Startup environment | 6 jobs Salary bonus | 6 jobs Parental leave | 5 jobs Competitive pay | 5 jobs Team events | 5 jobs Equity / stock options | 4 jobs Insurance | 4 jobs Gear | 3 jobs Relocation support | 2 jobs Medical leave | 2 jobs Home office stipend | 2 jobs 401(k) matching | 1 jobs Wellness | 1 jobs Conferences | 1 jobs Flexible spending account | 1 jobs

Salary Composition

The salary for a Mid-level 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 bulk of the total compensation package. Performance bonuses are often tied to individual or company performance metrics and can vary significantly. Additional remuneration, like stock options, is more common in tech companies, especially startups or large tech firms, and can be a significant part of the compensation in regions like Silicon Valley. In contrast, companies in other regions or industries might offer less in terms of stock options but may provide other benefits like health insurance, retirement plans, or educational reimbursements.

Steps to Increase Salary

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

• Skill Enhancement: Acquire advanced skills in AI/ML, such as deep learning, natural language processing, or computer vision. These skills are in high demand and can command higher salaries.
• Certifications: Obtain relevant certifications that can validate your expertise and make you more competitive.
• Networking: Engage with industry professionals through conferences, workshops, and online platforms to learn about new opportunities and trends.
• Advanced Education: Pursue a master's degree or specialized courses in data science or AI to deepen your knowledge and open up higher-level positions.
• Leadership Roles: Aim for leadership or managerial roles within your organization, which typically offer higher compensation.

Educational Requirements

Most mid-level Business Intelligence Engineer positions require at least a bachelor's degree in a related field such as Computer Science, Information Technology, Data Science, or Statistics. Some employers may prefer candidates with a master's degree, especially for roles that involve complex data analysis or machine learning tasks. A strong foundation in mathematics and statistics is also essential, as these are critical for data analysis and algorithm development.

Helpful Certifications

Several certifications can enhance your qualifications for a Business Intelligence Engineer role:

• Certified Business Intelligence Professional (CBIP): This certification is recognized in the BI field and covers a range of topics from data analysis to data warehousing.
• Microsoft Certified: Azure Data Scientist Associate: Useful if you work with Microsoft Azure, this certification demonstrates your ability to apply data science techniques on Azure.
• Google Professional Data Engineer: This certification is beneficial if you work with Google Cloud Platform and want to demonstrate your ability to design, build, and manage data processing systems.
• AWS Certified Data Analytics – Specialty: Ideal for those working with AWS, this certification validates your expertise in data analytics.

Experience Requirements

Typically, a mid-level Business Intelligence Engineer is expected to have 3-5 years of experience in a related field. This experience should include hands-on work with data analysis, data modeling, and the use of BI tools such as Tableau, Power BI, or Looker. Experience with SQL and programming languages like Python or R is also commonly required. Additionally, familiarity with machine learning concepts and tools can be advantageous.

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