We are seeking a hands-on
Fabric Data Integration Engineer
to design, build, and validate scalable data ingestion solutions using Microsoft Fabric and modern Azure data technologies. This role will focus on integrating data from APIs, files, databases, SFTP, batch processes, and real-time streaming sources into Microsoft Fabric.
The ideal candidate has recent experience with
Microsoft Fabric Pipelines, Dataflows Gen2, notebooks, and Eventstreams
, along with a strong understanding of raw-data landing patterns, metadata management, schema evolution, secure connectivity, and data recovery. Candidates with strong Azure Data Factory, Databricks, Event Hubs/Kafka, and Delta Lake experience may also be considered if they can demonstrate current exposure to Microsoft Fabric.
Duration of contract
: Through 12/31/2027 with high potential to extend into 2028
Location
: Remote with potential to need to go on site to Denver, CO from time to time.
Citizenship:
Must be a US Citizen. No 3rd parties. Compensation on W2 or 1099.
Key Responsibilities
Build ingestion solutions using Microsoft Fabric Pipelines, Dataflows Gen2, notebooks, and Eventstreams.
Integrate data from APIs, files, databases, SFTP, batch processes, and streaming sources.
Implement raw-data landing patterns, audit/load metadata, schema evolution, duplicate prevention, restart/replay, and failure recovery.
Configure secure connectivity using service principals, managed identities, gateways, workspace identities, and approved credential-management practices.
Review use cases, identify source owners and dependencies, and develop reusable architecture patterns and ingestion plans.
Develop POCs and wave plans to validate streaming sensor sources, scheduled partner APIs, and operational database integration using Fabric Mirroring/CDC where supported.
Required Qualifications
Hands-on experience with Microsoft Fabric data integration, particularly Pipelines, Dataflows Gen2, notebooks, and Eventstreams.
Experience with API, file, database, SFTP, batch, and streaming ingestion.
Strong understanding of raw-data landing, metadata, schema evolution, secure connectivity, and recovery patterns.
Ability to develop reusable solutions, troubleshoot integration issues, and collaborate with technical teams.
Preferred Qualifications
Recent Microsoft Fabric implementation experience.
Experience with Azure Data Factory, Databricks, Event Hubs/Kafka, and Delta Lake.
Familiarity with Fabric Mirroring, CDC, IoT/telemetry data, and near-real-time processing.
Ideal Candidate: A hands-on engineer who can build and troubleshoot ingestion solutions while helping establish scalable architecture and implementation plans. Candidates with strong Azure data engineering experience and demonstrable Microsoft Fabric exposure may also be considered.