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Lean Solutions Group

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Data Engineer

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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

Skills

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See also

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