Data Engineer

Joint Commission; Oak Brook (IL); On-site; USD 107,000 - 143,000; Full time

Benefits offered by this job

Comprehensive benefits

Job summary

Joint Commission is seeking a Data Engineer to design, develop, and optimize enterprise data pipelines and platforms using Azure Data Factory, Databricks, Foundry, and Microsoft Fabric. You will build scalable solutions supporting reporting, analytics, and operational needs, while ensuring data quality, security, and governance.

The role requires 5-7 years in data engineering with SQL and Python proficiency, and collaboration across analytics, BI, and business teams to translate requirements

Qualifications

• Bachelor's degree required in a related field.
• 5-7 years of data engineering, ETL/ELT, or cloud data platforms experience.
• Hands-on with Azure Data Factory, Databricks, Microsoft Fabric, and MSSQL.
• Strong knowledge of data lake, lakehouse, and data warehouse architectures.
• Proficiency in SQL and Python; familiarity with cloud platforms and big data.
• Ability to diagnose data issues and optimize performance.

Responsibilities

• Design, develop, and maintain scalable data pipelines.
• Build and optimize data ingestion, transformation, and integration processes.
• Develop data lakes, lakehouses, and data warehouses using MSSQL and cloud platforms.
• Implement ETL/ELT best practices for performance and data quality.
• Automate data workflows and monitor pipeline health.
• Collaborate with analytics, BI, and business teams to translate requirements into solutions.

Skills

SQL proficiency

Python programming

Cross-functional collaboration

Analytical thinking

Education

Bachelor's degree in Computer Science / Information Systems / Data Engineering

Tools

Azure Data Factory

Databricks

Microsoft Fabric

MSSQL

Data Lake / Lakehouse concepts

ETL/ELT

Job description

Overview

The Data Engineer is responsible for designing, developing, and optimizing enterprise data pipelines and data platforms. This role focuses on building scalable, efficient, and secure data solutions using modern cloud technologies. The engineer collaborates with analytics, BI, and business teams to transform requirements into reliable data assets that support reporting, analytics, and operational needs.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Azure Data Factory, Databricks, Foundry, and Microsoft Fabric.
• Build and optimize data ingestion, transformation, and integration processes across structured and unstructured data sources.
• Develop and support data lakes, lakehouses, and data warehouse environments using MSSQL and cloud-native platforms.
• Implement ETL/ELT best practices to ensure performance, reliability, and data quality.
• Automate data workflows and monitor pipeline health; identify and resolve issues promptly.
• Work closely with analytics, BI, and business teams to understand data requirements and translate them into technical solutions.
• Partner with cross-functional teams to support data-driven initiatives and ensure pipelines align with reporting and operational needs.
• Contribute to documentation of data structures, transformation logic, and system dependencies.
• Contribute to evaluating and adopting new tools, frameworks, and technologies that enhance data engineering efficiency and scalability.
• Follow standards for code quality, testing, version control, and documentation.
• Apply data governance, quality, and reliability principles in daily engineering work.
• Build reusable data models and curated datasets to enable self-service analytics.
• Ensure downstream BI teams receive accurate, well-structured, and timely data.
• Transform business requirements into scalable and maintainable technical designs.
• Ensure data engineering solutions align with privacy regulations such as GDPR and HIPAA, as well as internal security requirements.
• Maintain proper data access controls and contribute to monitoring data quality and compliance metrics.

Qualifications

Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field.

• 5-7 years of experience in data engineering, ETL/ELT development, or cloud data platforms.
• Hands-on experience with Azure Data Factory, Databricks, Microsoft Fabric, and MSSQL.
• Strong knowledge of data lake, lakehouse, and data warehouse architectures.
• Solid understanding of ETL/ELT processes, data modeling, and metadata management.
• Proficiency in SQL and Python; familiarity with cloud platforms and big data technologies.
• Ability to diagnose data issues, optimize performance, and work with cross-functional technical and business teams.

Preferred Certifications

• Microsoft Certified: Azure Data Engineer Associate
• Databricks Certified Data Engineer
• Certifications related to data governance, risk, or compliance
• Master's degree in Computer Science, Information Systems, or related fields

Benefits and Equal Opportunity

We offer a comprehensive benefit package. For a complete overview of our benefits package, please visit our Joint Commission Career Page

We are an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by law.

Salary

USD $107,000.00/year

USD $143,000.00/year