Business Intelligence Career Path: How to Get Started + Tips (Updated in 2025)

Business intelligence is one of the fastest-growing job sectors in the United States. According to the Bureau of Labor Statistics, hiring for business intelligence analysts is expected to grow by 14% over the next decade.

A business intelligence analyst career path generally has three tracks: Analytics, Engineer, or Architecture. Business intelligence analysts evaluate business data and generate insights to help businesses reduce costs, maximize profits, or gain a competitive edge. Business intelligence engineers, architects, and developers design and construct the infrastructure to store and process data.

To launch a business intelligence career, you will likely need a minimum of the following:

• A bachelor’s degree in computer science, analytics, or a related field.
• 4 years of professional experience (often in a related role like data or marketing analyst).
• Advanced SQL, database design, Tableau, analytics, and statistics skills.

This business intelligence analyst career path guide provides an overview of the field, introduces different BI job titles, and offers tips for breaking into business intelligence careers. You can also start by practicing these business intelligence interview questions.

Business Intelligence combines analytics, data mining, and data visualization. The chief function of BI is to translate data into insights that facilitate data-driven decision-making.

Here is an explanation by a current practitioner about the huge impact BI professionals have on their organizations:

“Business intelligence (also called BI) refers to the technology that allows businesses to organize, analyze, and contextualize business data from around the company,” says Ben Johnson, a Business Intelligence Analyst at Access Bank. “BI makes a difference by introducing options to summarize insights, making business operations smarter, providing visibility to facts concealed under complex data, and providing a competitive edge to business everywhere.”

Modern business intelligence systems utilize a mix of tools and processes, including:

• Data mining - Analysis of large datasets using statistics and machine learning.
• Dashboarding - Using dashboards to share visualizations and analysis with stakeholders for faster decision-making.
• KPIs and benchmarking - This is a key function of BI: Comparing current data to historical data to benchmark performance.
  
• Descriptive analytics - Answering questions using analytics data like: What happened? When did it happen? Who performed what? How many?
• ETL development - Building data infrastructure to process and prepare large volumes of data for analysis.

Within business intelligence, some developers and engineers build BI and analytics infrastructure, and analysts evaluate the data, meet with stakeholders, and generate reports that inform business decisions. Some of the most common job functions include:

• Meeting with stakeholders to determine BI needs.
• Collaborating cross-functionally to obtain feedback.
• Collecting and extracting data from warehouses for reporting.
• In-depth data analysis, using SQL and analytics solutions.
• Presenting reports and visualizations to key stakeholders.
• Developing analytics models and techniques that meet the company’s needs.

Solving a Business Intelligence Problem

Let’s say an e-commerce business is experiencing high abandoned cart rates. To solve this business intelligence problem, the BI department would first meet with stakeholders to determine the data types needed to scope out the issue at hand.

In this case, customer experience analytics could help identify where in the sales funnel customers abandoned their cart, which types of customers are abandoning, and potentially why they are abandoning. After meeting with stakeholders, a business intelligence engineer would design and build databases and dashboards to process the raw customer analytics data.

Then, a business intelligence analyst would analyze the aggregated data assembled by the engineer and identify where customers were dropping off in the sales funnel, which types of customers, etc. By reporting this information to the product and development teams, the analyst can help improve customer experiences, reduce abandonment rates, and drive new revenue.

Almost all business intelligence professionals start in analyst roles before working their way up the career ladder. The most common roles in business intelligence include:

• Business Intelligence Analyst - BI analysts typically deal with processed data. They perform statistical analysis to generate reports and isolate insights about the business. They typically focus on marketing, operations, or finance for the business.

• Customer Insight Analyst - This role is common in larger companies (like Amazon) and is an analytics role focused solely on customer experiences. Customer insight analysts typically serve customer experience and marketing departments to help them better understand their core customers and answer questions about how to best serve the customer’s needs.

• Business Intelligence Engineer - Like the data engineer role, BI engineers build dashboards, databases, and ETL pipelines to process raw analytics data. They are also responsible for using visualization tools like Tableau to implement dashboards for stakeholders.

• Business Intelligence Developer - BI developers have a similar role to engineers. Still, developers typically work more closely on front-end solutions, helping to develop dashboards, software, and applications to present business data.

• Business Intelligence Architect - In large organizations, BI architects are responsible for designing a roadmap for development. Architects are not necessarily responsible for building or implementing the solutions; rather, they are responsible for translating the needs of an organization into a plan for the developers and engineers to build.

• Business Intelligence Manager - Business intelligence managers oversee a team of analysts and developers/engineers, and they are responsible for driving the performance of the BI department. Managers collaborate cross-functionally with leadership teams, building and interacting with stakeholders to shape the BI development and analysis roadmap.

In simple terms, business intelligence, or BI, is the practice of applying data insights to running an enterprise business. This field is split between two common careers (BI analysts and BI engineers).

While there is some overlap between the two roles, a BI engineer mainly constructs and maintains the data pipeline a BI analyst uses to deliver insights to their employer. Therefore, BI engineers have a more technical role than BI analysts, requiring specialization in data storage and ETL tools.

What Does a Business Intelligence Analyst Do?

The core responsibility of a business intelligence analyst is to gather, clean, and analyze business data. This can include data like revenue, sales, or customer engagement metrics. In particular, BI analysts are required to:

• Interpret data - Analysts are tasked with identifying patterns and anomalies that signal an area for improvement. A BI analyst, for example, might analyze customer engagement data to determine optimization techniques for a sales funnel.
• Share findings - BI analysts regularly present their work to stakeholders, product teams, and leadership. Analysts may be required to build visualizations or present reports to make their insights more accessible.
• Make recommendations - Based on their analyses, BI analysts also make recommendations to help the business become more efficient or grow.

What Does a Business Intelligence Engineer Do?

Business intelligence engineers and developers’ core responsibility is building and maintaining the BI data environment. They may create pipelines to process daily transaction data or develop custom BI reporting tools. Responsibilities of a business intelligence engineer include:

• Data architecture - BI engineers develop the frameworks for storing and processing data, including databases, data warehouses, and pipelines.
• BI development - Engineers design, implement, and maintain BI tools that facilitate analysis, including reports and dashboards.
• Customizing BI platforms - Engineers may also be tasked with adding new capabilities to existing BI platforms or developing new BI tools and platforms for the company.

No matter the role, careers in business intelligence require a strong background in business, economics, statistics, or a related field. BI professionals also require strong technical skills, as well as the ability to communicate their insights to people who may not be familiar with data science.

Required business intelligence skills include:

Non-Technical Skills

• Exceptional verbal and written communication/presentation skills to share technical insights and recommendations with colleagues in an easy-to-understand manner.
• Project management and leadership skills, as well as the ability to work effectively in a team.
• Problem-solving skills and critical thinking.
• Ability to operate in a workforce targeted at consumer satisfaction. Many roles, especially BI analysts, will be called to work with external partners and clients.

Technical Skills

• Expert knowledge of SQL
• Knowledge of Python
• Cloud computing and data storage technology such as Google’s Big Query and Amazon’s Redshift
• Database design and data architecture
• Data security and privacy
• Data mining and visualization, including Tableau, Microsoft Power BI, or QuickSight
• Business intelligence tools like Hyperion, MicroStrategy, or Cognos

A bachelor’s degree is a minimum requirement to land a BI job. However, most BI jobs are not entry-level and require 4 years of professional experience on average.

With that professional experience component in mind, it is important to choose a major that provides skills well-aligned with BI careers and will help you land an entry-level role like a data analyst. The best subjects to study for BI careers include:

• Statistics or applied math
• Computer science
• Engineering (Computer/electrical/industrial)
• Economics
• Business (with a technology-related minor)

Do You Need a Master’s Degree?

Beyond a bachelor’s degree, you will likely need supplemental training for the role. In fact, a master’s degree is an increasingly common ‘preferred’ qualification for business intelligence jobs. There are two ways you can gain additional training:

• Professional certifications - Certificate programs in SQL, data analytics, and visualization tools like Tableau, QuickSight, and Python will make you more competitive for BI roles. Boot camps can also help you level up your skills in a short amount of time.

• Master’s degree - A master’s degree in statistics, data analytics, data science, or a related quantitative field is preferred for many BI roles. MBAs are another option but would require additional training in BI technology. Typically, a master’s degree is helpful for those making career transitions or those who want a deeper understanding of data science.

As we have discussed, a BI analyst is not an entry-level role. This is because employers prefer analysts who have solid experience in data and business analysis. Having an MBA or data science master’s can substitute for a portion of real-world experience; however, you should still expect to be asked for 1-2 years in the field besides the degree.

Since most BI roles require 4 or more years of professional experience, many BI analysts, engineers, and developers start their careers as data analysts, business analysts, or entry-level data engineering jobs.

These roles provide a strong foundation in skills like SQL, data analytics, and database design, which are all must-have foundations for BI roles. Similarly, these roles provide an introduction to tools like Tableau, AWS Glue, and Hadoop.

Building Business Intelligence Skills

Other than working for a company, you can build business intelligence skills in many ways. You can:

• Study business intelligence interview questions and develop your ability to answer these questions in interviews
• Work on business intelligence projects using existing datasets
• Master SQL and data analytics
• Consider a certification, boot camp or a master’s degree

Preparing for Business Intelligence Interviews

Ultimately, no matter your mix of experience and outside learning, you must do well in the interview. Business intelligence interviews focus heavily on SQL, as well as analytics and SQL case studies, product/business sense, and statistics. For example, the Amazon business intelligence engineer interview includes 4-5 rounds that focus on:

• Statistics and SQL technical interview with a Business Intelligence Engineer. This interview assesses your SQL and basic statistics knowledge. It also has some behavioral elements to it.
• Behavioral plus SQL interview with some case-based questions around leadership principles.
• Case study interview and behavioral interview with a hiring manager.
• Behavioral Interview with a focus on leadership principles.
• Statistics and Product-Sense interview with a data scientist. This interview round assesses your basic knowledge of data science concepts and metric definitions.

Business case studies are a key part of BI interviews, and they help to practice with as many mock interviews as possible. Here is one such example: a walk-through of a business intelligence mock interview:

A senior-level BI analyst role typically requires at least eight years of experience in business intelligence, analytics, product management/development, or technology. In addition, for senior-level roles, an MBA or master’s degree in data science, business analytics, or statistics is often required. Besides experience and a higher education, some employers also require Certified Business Analysis Professional certification through the International Institute of Business Analysis.

Here is a complete list of requirements for a senior-level BI role:

• A working knowledge of data mining principles, predictive analytics, mapping, and collecting data from multiple data systems on-premises and cloud-based data sources.
• Strong SQL skills and ability to perform effective querying involving multiple tables and subqueries.
• Understanding of and experience using analytical concepts and statistical techniques. These include hypothesis development, designing tests/experiments, analyzing data, drawing conclusions, and developing actionable recommendations for business units.
• Strong programming skills with querying languages: SQL, SAS, etc.
• Experience with data visualization tools: Tableau, Power BI, Metabase, chart.js, etc.
• Strong ability to manage numerous processes and projects simultaneously.
• Experience working with and creating databases and dashboards using all relevant data to inform decisions.

Business intelligence manager roles typically require an MBA or master’s degree in business analytics. Similarly, these roles require 10-12 years of BI or related experience, and employers may also request some form of BI certification.

BI managers generally work closely with leaders across operations, product, business development, and other related departments to support and implement tools that facilitate more agile data-driven decision-making. The key role of a BI manager is to lead the BI team - including analysts, engineers, and developers. Managers are integral in conceptualizing, building, maintaining, and generating insights from the organization’s BI tools.

Some requirements include:

• Experience in planning and coordinating organizational analytics systems’ development, design, and implementation.
• Experience managing data warehouse and reporting infrastructure to help scale reporting needs while maintaining a high-performance reporting environment.
• Understanding of reporting and business intelligence best practices.
• In-depth knowledge and understanding of data governance best practices.
• Experience in people management and/or project management.
• Experience building and maintaining an enterprise data warehouse.
• Strong communication and collaboration skills.

Interview Query offers a variety of resources to help you prepare for business intelligence interviews. Start with our guide to Business Intelligence Interview Questions, or become a premium member to access:

• 500+ Real Data Science Interview Questions
• Data Science Interview Course (with modules in Product Sense, Analytics/SQL, and Statistics)
• Practice Take-Home Exercises
• Data Science Skills Tests
• Data Science Case Studies
• Data Science Projects