Transportation Data Analytics Lead - Hybrid & High-Impact

VHB; Washington (District of Columbia); Hybrid; USD 145,000 - 195,000; Full time

Benefits offered by this job

Total Rewards Program

401(k) plan

Health benefits

Hybrid work environment

Professional development

Job summary

VHB is seeking a Transportation Data Analytics Lead to drive enterprise analytics across transportation projects. You will lead a cross-disciplinary team of engineers, scientists, planners, and technologists in delivering data-driven solutions for public and private sector clients.

The role emphasizes building scalable dashboards, data platforms, and predictive models while advancing data governance, quality, and innovative analytics methodologies within a collaborative, hybrid environment.

Qualifications

• Minimum 8+ years of advanced analytics in engineering/transportation industry for DOTs, agencies, or government.
• Master's degree or equivalent in a relevant field; or extensive related experience.
• Experience leading large-scale transportation analytics programs and teams.
• Experience with data governance and scalable analytics frameworks.

Responsibilities

• Lead enterprise transportation data analytics initiatives across multiple service lines.
• Build and mentor high-performing data analysts and specialists.
• Oversee design and deployment of dashboards, data platforms, and reporting tools.
• Define data architecture, governance, and quality assurance across complex datasets.

Skills

Data analytics leadership

Databricks

SQL

Power BI

Python/R

Education

Master's degree in Data Science/Engineering/Analytics

Tools

Cloud data platforms

APIs

ETL pipelines

Job description

VHB is seeking a Transportation Data Analytics Lead to drive enterprise analytics across transportation projects. You will lead a cross-disciplinary team of engineers, scientists, planners, and technologists in delivering data-driven solutions for public and private sector clients.

The role emphasizes building scalable dashboards, data platforms, and predictive models while advancing data governance, quality, and innovative analytics methodologies within a collaborative, hybrid environment.