Business Intelligence Engineer

A Business Intelligence Engineer designs and develops data pipelines and ETL processes, ensuring data quality, availability, and accessibility for business intelligence solutions.
Salary Insights
High-ROI Certifications
Potential Lateral Jobs
Publications/ Groups

Business Intelligence Engineer

Glassdoor
Market
National (USA)
Base Salary
$105,209 / year
Satisfaction
Additional Benefits
Yes
Industry
All
Education
Bachelor's Degree

The average salary for Business Intelligence Engineer is $105,209 / year according to Glassdoor.com

There are no updated reports for Business Intelligence Engineer salaries. You can check potential lateral job opportunities in this information stack to find related salary information.

Business Intelligence Engineer role may have an alternate title depending on the company. To find more information, you can check Glassdoor.com.

Career Information

As a Business Intelligence Engineer, you will be responsible for designing and developing data pipelines and analytics solutions for organizations. You will need a strong understanding of data engineering, data modeling, and business intelligence tools, as well as experience with programming languages like Python or SQL. Strong problem-solving and technical skills are essential, as you will be responsible for transforming raw data into actionable insights and delivering scalable data solutions.

The average salary for Business Intelligence Engineer is $105,209  / year according to Glassdoor.com
AI Disclaimer
The following text about the Job role of Business Intelligence Engineer has been generated by an AI model developed by Cohere. While efforts have been made to ensure the accuracy and coherence of the content, there is a possibility that the model may produce hallucinated or incorrect information. Therefore, we strongly recommend independently verifying any information provided in this text before making any decisions or taking any actions based on it.

At a high level, Business Intelligence (BI) Engineers are responsible for designing and developing business intelligence solutions to help organizations make informed business decisions. They are involved in the entire lifecycle of a business intelligence project, from initial requirements gathering and design to development, testing, and deployment.

Most importantly, a Business Intelligence Engineer must have strong analytical and problem-solving skills, as well as the ability to work with large data sets and complex business processes. They must also be able to communicate effectively with business and technical stakeholders, as well as be able to work independently and as part of a team.

Here are some of the most important skills and tasks that a Business Intelligence Engineer is responsible for:

  • Designing and developing business intelligence solutions, including dashboards, reports, and data visualizations
  • Collecting, organizing, and analyzing large data sets from multiple sources
  • Creating and maintaining data models and data warehouses
  • Developing and testing business intelligence software and tools
  • Deploying and maintaining business intelligence solutions
  • Conducting training and providing support for business intelligence users
  • Staying up-to-date on industry trends and best practices

A Business Intelligence Engineer must have a strong understanding of business processes and the ability to translate business requirements into technical solutions. They must also be able to work with a variety of technologies, including SQL, data visualization tools, and business intelligence software.

In addition to these technical skills, a Business Intelligence Engineer must have strong communication and interpersonal skills, as well as the ability to work effectively in a team environment. They must also be able to manage their time and priorities effectively, as well as be able to work on multiple projects simultaneously.

Overall, a Business Intelligence Engineer is a critical member of any organization's business intelligence team, and their skills and expertise are essential for the successful implementation of business intelligence solutions.

Potential Lateral Jobs
Explore the wide range of potential lateral job opportunities and career paths that are available in this role.

High-ROI Programs

Most roles require at least a bachelor's degree. To remain competitive, job seekers should consider specialization or skill-specific programs such as specialization, bootcamps or certifications.
Certification Programs
Consider pursuing specialized certifications or vendor-specific programs to enhance your qualifications and stand out in the job market.

Databricks Certified Data Engineer Associate

The Databricks Data Engineer Certification program is highly sought after, designed to evaluate an individual's proficiency in utilizing the Databricks Lakehouse Platform for performing fundamental data engineering tasks.

Intermediate
View More

Microsoft Certified: Azure Data Engineer Associate

DP-203

The Microsoft Certified: Azure Data Engineer Associate program is designed for professionals who have expertise in integrating, transforming, and consolidating data from various structured, unstructured, and streaming data systems.

Intermediate
View More

Google Certified Professional Data Engineer

The Google Certified Professional Data Engineer is a high-ROI program designed for experienced professionals to become highly equipped with specialty skills and functional knowledge in cloud data engineering.

Advanced
View More

AWS Certified Data Analytics — Specialty

DAS-C01

The AWS Data Analytics Certification program validates a deep understanding of AWS data analytics services and their integration with each other to derive insights from data, making it suitable for individuals pursuing a role focused on data analytics.

Advanced
View More

Microsoft Certified: Azure Enterprise Data Analyst Associate

DP-500

The Azure Data Analyst Certification is a high-ROI program designed for professionals who have expertise in designing, creating, and deploying enterprise-scale data analytics solutions.

Intermediate
View More

AWS Certified Machine Learning — Specialty Certification

MLS-C01

The AWS Certified Machine Learning - Specialty certification covers a wide range of topics, including data engineering, exploratory data analysis, modeling, and machine learning implementation and operations on the AWS Cloud. 

Advanced
View More

Google Certified Professional Machine Learning Engineer

The Google Machine Learning Certification is a high-ROI program designed for ML engineers who want to gain specialized machine learning skills using Google Cloud technologies.

Advanced
View More
Specialization Programs improving
If you want to improve your skills and knowledge in a particular field, you should think about enrolling in a Nanodegree or specialization program. This can greatly improve your chances of finding a job and make you more competitive in the job market.

Mathematics for Machine Learning and Data Science Specialization

Specialization

Introduction to Data Science

Specialization

Deep Learning Specialization

Specialization

IBM Data Analyst Professional Certificate

Professional

Genomic Data Science Specialization

Specialization

IBM Data Warehouse Engineer Professional Certificate

Professional

Google Business Intelligence Professional Certificate

Professional

Data Analyst with Python

Career Track

Advanced Statistics for Data Science Specialization

Specialization

This specialization equips you with essential concepts in probability, statistics, data analysis, matrix algebra, and linear models for Data Science.

Advanced Linear Models for Data Science 2: Statistical Linear Models

Course

This course delves deeper into expected values, multivariate normal distribution, distributional results, and residuals, enhancing your data science models with a strong foundation in R and college-level statistics and math.

Advanced Linear Models for Data Science 1: Least Squares

Course

This course provides a solid foundation in linear algebraic treatment of regression modeling, equipping learners with sound data science skills in linear regression, R programming, and linear algebra.

Data Science: Statistics and Machine Learning Specialization

Specialization

This comprehensive course equips you with essential Statistical and Machine Learning skills for Data Science, including R Programming, Regression Analysis, Data Visualization, and Random Forest.

Intermediate
View More
View More

Statistical Modeling for Data Science Applications Specialization

Specialization

This specialization enhances your Data Science skills by teaching advanced statistical modeling techniques, including Linear Models, R Programming, Regression, Calculus, Probability, and Linear Algebra.

Intermediate
View More
View More

Intermediate Statistical Modeling in R

Course

This course delves into sampling variability, mathematical transforms, collinearity implications, effect size, interaction, and understanding total and partial change to enhance your R Programming skills.

Intermediate
View More
View More

Introduction to Statistical Modeling in R

Course

This course delves into essential statistical methodologies using R programming, equipping you with the skills to design, train, and evaluate models while assessing prediction performance and exploring data with covariates and effect size.

Intermediate
View More
View More

Resource Stacks

We are soon crowdsourcing these resource stacks to collate the best resources, such as publications, community groups, job boards, etc., that are practically suitable for every contextual stack.
Publications
Discover the wide array of publications that professionals in this role actively engage with, expanding their knowledge and staying informed about the latest industry trends and developments.
Communities updating
Discover the thriving communities where professionals in this role come together to exchange knowledge, foster collaboration, and stay at the forefront of industry trends.
Research updating
We are currently in the process of updating contextual resources and we will be adding the new ones to the list shortly.
AI Disclosure: We are testing AI technologies to ensure the accuracy and coherence of recommendations. However, it is important to note that there is a possibility that the model may create hallucinated or incorrect inferences. Therefore, we highly recommend independently verifying any information provided in these stacks before making any decisions or taking any actions based on it.
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