Remote Platform Data Analyst - Transport & BI

Lineage

United States

Remote

USD 110,000 - 160,000

Full time

10 days ago

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Job summary

Lineage is seeking a Platform Data Analyst for a fully remote role. The analyst will translate transport data requirements into robust data models, schemas, and semantic layers supporting global data warehousing and analytics.

The role collaborates with product SMEs and the Global TMS Data Architect to ensure data is well-structured, well-documented, and ready for reporting, with emphasis on data quality and governance.

Qualifications

  • Bachelor’s degree in CS/IS or related field or equivalent experience.
  • 5–8 years in data analytics, data engineering, or BI roles.
  • Experience with global/multi-region implementations preferred.
  • Transport, logistics, or supply chain domain knowledge is a plus.
  • Strong SQL and data modeling skills.

Responsibilities

  • Translate data requirements into data models, schemas, and semantic layers for the data warehouse.
  • Create ERDs and data matrices for transport applications.
  • Document semantic layers aligned to business processes and reporting needs.
  • Define data lineage and integration points between platforms and the central data warehouse.
  • Collaborate with the Global Reporting Lead on analytics and self-service reporting.

Skills

SQL & DB design
Data modeling ERD
ETL concepts
Data warehouse design
Communication skills
Requirements gathering
Blue Yonder TMS familiarity
BI tools (Power BI, Sigma, Tableau)

Education

Bachelor's degree in CS/IS or related field
5-8 years in data analysis/BI roles

Tools

Erwin
Lucidchart

Job description

Lineage is seeking a Platform Data Analyst for a fully remote role. The analyst will translate transport data requirements into robust data models, schemas, and semantic layers supporting global data warehousing and analytics.

The role collaborates with product SMEs and the Global TMS Data Architect to ensure data is well-structured, well-documented, and ready for reporting, with emphasis on data quality and governance.

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