BI Engineer Salary in United States during 2024

Salary details

The average BI Engineer salary lies between USD 100,000 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: Dec. 1, 2024

Top 20 Job Tags for BI Engineer roles

The three most common job tag items assiciated with BI Engineer job listings are SQL, Power BI and Engineering. 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 | 175 jobs Power BI | 144 jobs Engineering | 136 jobs Business Intelligence | 125 jobs Computer Science | 98 jobs Python | 95 jobs ETL | 90 jobs Pipelines | 89 jobs Tableau | 88 jobs AWS | 84 jobs Azure | 64 jobs GCP | 63 jobs Data quality | 63 jobs Security | 62 jobs Agile | 60 jobs Data Analytics | 59 jobs Testing | 59 jobs Architecture | 55 jobs Snowflake | 51 jobs Data Warehousing | 48 jobs

Top 20 Job Perks/Benefits for BI Engineer roles

The three most common job benefits and perks assiciated with BI Engineer job listings are Career development, Flex hours and Team events. 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 | 140 jobs Flex hours | 98 jobs Team events | 67 jobs Health care | 63 jobs Competitive pay | 46 jobs Flex vacation | 42 jobs Salary bonus | 40 jobs Startup environment | 35 jobs Equity / stock options | 32 jobs Medical leave | 32 jobs Insurance | 26 jobs Parental leave | 25 jobs 401(k) matching | 16 jobs Wellness | 16 jobs Conferences | 10 jobs Home office stipend | 10 jobs Fitness / gym | 8 jobs Transparency | 8 jobs Unlimited paid time off | 6 jobs Relocation support | 5 jobs

Salary Composition

In the United States, the salary composition for a BI Engineer transitioning into AI/ML/Data Science roles can vary significantly based on region, industry, and company size. Typically, the salary is composed of a fixed base salary, which forms the bulk of the compensation package. This base salary can range from 70% to 85% of the total compensation. Bonuses, which can be performance-based or company-wide, often account for 10% to 20% of the total package. Additional remuneration may include stock options, especially in tech companies, and other benefits such as health insurance, retirement contributions, and professional development allowances. In tech hubs like Silicon Valley or New York, the total compensation might be higher due to the cost of living and competitive job market. Conversely, in smaller markets or less tech-centric industries, the base salary might be lower, but the overall package can be balanced with other benefits.

Steps to Increase Salary

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

• Skill Enhancement: Continuously update your skills in AI/ML and data science. Mastering advanced techniques and tools can make you more valuable.
• Specialization: Focus on a niche area within AI/ML, such as natural language processing or computer vision, which can command higher salaries.
• Networking: Build a strong professional network. Attend industry conferences, join relevant online communities, and connect with thought leaders.
• Advanced Education: Pursue further education, such as a master's degree or Ph.D., which can open doors to higher-paying roles.
• Leadership Roles: Aim for leadership or managerial positions, which typically offer higher compensation.
• Company Change: Sometimes, moving to a different company can result in a significant salary increase, especially if the new company values your specific skill set more.

Educational Requirements

Most AI/ML/Data Science roles require at least a bachelor's degree in a related field such as computer science, data science, mathematics, or engineering. However, many employers prefer candidates with a master's degree or even a Ph.D. in these fields, as advanced education often correlates with a deeper understanding of complex algorithms and data analysis techniques. Additionally, coursework in statistics, machine learning, and programming is highly beneficial.

Helpful Certifications

Certifications can bolster your resume and demonstrate your commitment to the field. Some valuable certifications include:

• Certified Data Scientist (CDS)
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate
• AWS Certified Machine Learning – Specialty
• TensorFlow Developer Certificate

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

Required Experience

Typically, employers look for candidates with at least 3-5 years of experience in data-related roles. This experience should include hands-on work with data analysis, data modeling, and familiarity with AI/ML tools and frameworks. Experience in a BI role is advantageous, as it provides a strong foundation in data handling and business acumen, which are crucial for AI/ML roles.

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