Traffic & Revenue Forecast Engineer

Ferrovial Construction; Austin (TX); On-site; USD 90,000 - 120,000; Full time

Job summary

Ferrovial Construction is seeking a Traffic & Revenue Engineer in Austin, TX to analyze traffic and socioeconomic data and build forecasts for Cintra’s North American concessions. You will develop long-term revenue projections and contribute to feasibility studies, working with cross-functional teams to implement data-driven insights.

Ideal candidates have a civil engineering background with 1–3+ years in transportation analysis, strong Excel and coding skills (Python/SQL), and the ability to

Qualifications

• Experience in transportation analysis and data interpretation.
• Knowledge of traffic and revenue forecasting methods.
• Strong writing and verbal communication of technical concepts.
• Experience with data mining or econometrics is a plus.

Responsibilities

• Analyze traffic and socioeconomic data for forecasting.
• Build spreadsheet-based models to project traffic and revenue.
• Prepare memos and forecasts for supervisors and executives.
• Stay updated on regional policies and market trends.
• Define data collection programs (counts, surveys, polls).
• Collaborate with business development on feasibility analyses.
• Develop expertise in Cintra’s North American concessions.
• Prepare monthly reports on traffic, revenue, and economic conditions.

Skills

Highly motivated

Strong critical thinking

Organizational skills

Multitasking & problem solving

Quantitative skills

Technical communication

Excel proficiency

Coding in Python or similar

Education

Bachelor’s degree in Civil Engineering or related field

Transportation engineering coursework

Tools

ArcGIS

TransCAD

Cube

SQL

Python

MATLAB

Job description

Ferrovial Construction is seeking a Traffic & Revenue Engineer in Austin, TX to analyze traffic and socioeconomic data and build forecasts for Cintra’s North American concessions. You will develop long-term revenue projections and contribute to feasibility studies, working with cross-functional teams to implement data-driven insights.

Ideal candidates have a civil engineering background with 1–3+ years in transportation analysis, strong Excel and coding skills (Python/SQL), and the ability to