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How much do business intelligence data engineer jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for business intelligence data engineer in the United States is $57.05, according to ZipRecruiter salary data. Most workers in this role earn between $49.04 and $63.70 per hour, depending on experience, location, and employer.

What is a business intelligence data engineer?

A Business Intelligence (BI) Data Engineer is a professional responsible for designing, building, and maintaining the infrastructure and processes that allow organizations to collect, store, and analyze data for business decision-making. They work closely with data analysts, data scientists, and business stakeholders to ensure data is accessible, reliable, and optimized for reporting and analytics. Typical tasks include developing data pipelines, integrating data from various sources, and ensuring data quality and security. Their work enables organizations to transform raw data into actionable insights that help drive business growth.

What are the key skills and qualifications needed to thrive as a business intelligence data engineer?

To thrive as a Business Intelligence Data Engineer, you need strong skills in data modeling, ETL development, SQL, and a background in computer science or a related field. Proficiency with BI tools (e.g., Tableau, Power BI), data warehousing platforms (like Snowflake or Redshift), and certifications such as Microsoft Certified: Data Analyst Associate are highly valuable. Analytical thinking, problem-solving, and effective communication are important soft skills for translating business requirements into actionable insights. These competencies ensure reliable data infrastructure, accurate reporting, and successful collaboration with stakeholders to drive informed business decisions.

How do business intelligence data engineers typically collaborate with analysts and business stakeholders?

Business Intelligence Data Engineers frequently work alongside data analysts and business stakeholders to ensure data pipelines and reporting tools meet organizational needs. They translate business requirements into technical specifications, build or optimize data models, and provide clean, reliable datasets for analysis. Regular communication and feedback loops are essential, as data engineers must adapt solutions to evolving business questions and ensure data integrity throughout the process. This collaborative approach helps deliver actionable insights and supports data-driven decision-making across teams.

What is the difference between Business Intelligence Data Engineer vs Data Analyst?

AspectBusiness Intelligence Data EngineerData Analyst
Primary FocusBuilding and maintaining data pipelines and infrastructure for BI systemsAnalyzing data to generate reports and insights
Skills & CertificationsSQL, ETL tools, data warehousing, cloud platformsSQL, Excel, data visualization tools
Work EnvironmentData engineering teams, BI platforms, cloud environmentsBusiness units, reporting tools, dashboards
Industry UsageOrganizations with large data infrastructure needsOrganizations focusing on data-driven decision making

While both roles work with data, Business Intelligence Data Engineers focus on creating and managing the data infrastructure that enables BI reporting, whereas Data Analysts interpret data to provide actionable insights. Understanding these differences helps organizations assign the right roles for their data needs.

What cities are hiring for Business Intelligence Data Engineer jobs?

Cities with the most Business Intelligence Data Engineer job openings:

What states have the most Business Intelligence Data Engineer jobs?

States with the most job openings for Business Intelligence Data Engineer jobs include:

Business Intelligence Data Engineer jobs near you
Infographic showing various Business Intelligence Data Engineer job openings in the United States as of August 2026, with employment types broken down into 84% Full Time, 13% Part Time, and 3% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $118,660 per year, or $57 per hour.

Business Intelligence - Data Engineer 133-2016

CommunityCare

Tulsa, OK • On-site

$104K - $125K/yr

Full-time

Re-posted yesterday

Job description

JOB SUMMARY:
The Data Engineer will be responsible for expanding, optimizing and monitoring our data and data pipeline architecture, as well as optimizing data flow and collection across organizational teams. The Data Engineer will support our software engineers, database architects and data analysts on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.
KEY RESPONSIBILITIES:
  • Create and maintain optimal data pipeline architecture to support our next generation of products and data initiatives.
  • Assemble large, complex data sets that meet functional business requirements.
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
  • Experience in the development of SSIS, ETL and other standardized data management tools.
  • Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
  • Performs other job-related duties as required.

QUALIFICATIONS:
  • Build processes supporting data transformation, data structures, metadata, dependency and workload management.
  • Strong project management and organizational skills.
  • Ability to work independently, handle multiple tasks and projects simultaneously.
  • Successful completion of Health Care Sanctions background check.

EDUCATION/EXPERIENCE:
  • College degree or equivalent experience required.
  • Project management skills preferred.
  • Willingness to work in a high-tech, continually evolving, innovative environment.

CommunityCare is an equal opportunity at will employer and does not discriminate against any employee or applicant for employment because of age, race, religion, color, disability, sex, sexual orientation or national origin

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