Data Mesh Engineer – Microsoft Fabric & Real-Time Pipelines

DataJobs; Kansas City (MO); On-site; USD 110,000 - 160,000; Full time

Benefits offered by this job

Benefits package: Professional Non-UN

Job summary

JE Dunn is seeking an IT Data Engineer to build a scalable data foundation using Microsoft Fabric, focusing on enterprise data architecture, reliable pipelines, and trusted data. The role partners with data consumers and source system owners to ensure data quality, accessibility and interoperability for analytics and ML workflows.

Responsibilities include implementing a data mesh, real-time and batch integrations, API connections, governance, security, and comprehensive documentation.

Qualifications

• Bachelor’s degree in computer science, data engineering, data science or related field.
• Excellent communication, written and verbal.
• Strong time management and ability to prioritize multiple projects.
• Ability to drive change through innovation and process improvement.

Responsibilities

• Design and implement a data mesh architecture using Microsoft Fabric OneLake Lakehouses with data governance and security measures.
• Create and maintain data transformation processes to drive data quality and consistency.
• Develop and run synchronous (real-time) and batch integration processes with unidirectional and bidirectional data flows.
• Implement API and delta connections to enable system interoperability.
• Use data validation to support reliable data exchange between systems.
• Monitor system performance, compute resources, and storage utilization; troubleshoot pipeline failures.

Skills

SQL

Python

Spark

Power BI

REST APIs

Data governance

Microsoft Fabric

Data mesh

Data quality

Education

Bachelor’s degree in Computer Science / Data Engineering or related field

Tools

Microsoft Purview

OneLake Lakehouses

Job description

JE Dunn is seeking an IT Data Engineer to build a scalable data foundation using Microsoft Fabric, focusing on enterprise data architecture, reliable pipelines, and trusted data. The role partners with data consumers and source system owners to ensure data quality, accessibility and interoperability for analytics and ML workflows.

Responsibilities include implementing a data mesh, real-time and batch integrations, API connections, governance, security, and comprehensive documentation.