Data Engineer
About The Position
The Data Engineer designs, develops, and optimizes enterprise data pipelines and data platforms, focusing on scalable, efficient, and secure solutions using modern cloud technologies. The role collaborates with analytics, BI, and business teams to turn requirements into reliable data assets that support reporting, analytics, and operational needs. The position develops and maintains pipelines, data lakes, lakehouses, and data warehouses; supports data quality, governance, reliability, and compliance; and enables self-service analytics through reusable data models and curated datasets. It also contributes to technology evaluation, documentation, testing, and adoption of engineering best practices.
Requirements
- 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 and optimize performance.
- Ability to work with cross-functional technical and business teams.
Nice To Haves
- Microsoft Certified: Azure Data Engineer Associate certification.
- Databricks Certified Data Engineer certification.
- Certifications related to data governance, risk, or compliance.
- Master’s degree in Computer Science, Information Systems, or a related field.
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 support performance, reliability, and data quality.
- Automate data workflows, monitor pipeline health, and identify and resolve issues promptly.
- Work 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 align pipelines with reporting and operational needs.
- Document data structures, transformation logic, and system dependencies.
- Contribute to evaluating and adopting tools, frameworks, and technologies that improve engineering efficiency and scalability.
- Follow standards for code quality, testing, version control, and documentation.
- Apply data governance, quality, and reliability principles in engineering work.
- Build reusable data models and curated datasets to enable self-service analytics.
- Provide downstream BI teams with accurate, well-structured, and timely data.
- Transform business requirements into scalable and maintainable technical designs.
- Ensure solutions align with GDPR, HIPAA, and internal security requirements.
- Maintain appropriate data access controls and contribute to monitoring data quality and compliance metrics.
Benefits
- Joint Commission offers a comprehensive benefits package; details are available on its Career Page.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
