Data Engineer
Summary
Data Engineer on Lean Solutions Group's Performance Management & BI team, building and maintaining data pipelines and lakehouse architecture in Microsoft Fabric, integrating data from CRMs, APIs, and SaaS apps, and powering Power BI reporting and analytics. Remote, full-time role aligned with U.S. business hours.
Lean Solutions Group is a workforce optimization company supporting U.S. logistics, freight brokerage, factoring, and related industries through nearshore and offshore teams, technology, and data-driven solutions.
We are looking for a Data Engineer to join our Performance Management & Business Intelligence team and contribute to the development and operation of the data foundation that supports reporting, analytics, and business decision-making.
Key Responsibilities
- Build and maintain data pipelines and lakehouse architecture using Microsoft Fabric.
- Integrate data from CRMs, APIs, SaaS applications, SharePoint, Excel, and internal systems.
- Develop and maintain Bronze, Silver, and Gold data layers.
- Design data models and datasets for analytics and Power BI.
- Implement data quality checks, monitoring, validation, and alerting.
- Support data governance, lineage, security, and access management.
- Automate data processes and support CI/CD and release management.
- Collaborate with BI, Performance Management, Workforce Management, IT, Finance, and client teams.
Requirements
- 3+ years of hands-on Data Engineering experience.
- Strong SQL and Python skills, including PySpark.
- Experience with Microsoft Fabric or a comparable lakehouse platform such as Databricks, Synapse, or Azure Data Factory.
- Experience with data modeling, data pipelines, APIs, and automation.
- Working knowledge of Power BI and semantic models.
- Experience with data quality, governance, monitoring, and version control.
- Strong written and verbal English communication skills.
Experience working with BPO, logistics, contact center, workforce management, or shared services data is preferred.
Modality: Remote
Schedule: Full-time, aligned with U.S. business hours