Computational Water Resources Engineer

Description

Schnabel is an employee-owned, professional engineering and consulting firm that focuses on solving problems related to the earth and environment through specialization in geotechnical, geostructural, tunnel, and dam engineering. Schnabel’s high standards for quality, business ethics, and concern for the communities in which we live are a vital part of who we are. Schnabel is an ENR Top 500 Design Firm with 700+ employees in 32 offices throughout the United States.

Recognized by CE News as one of the Best Engineering Firms to Work for, Schnabel provides employees with a competitive benefits package including maternity leave, tuition reimbursement for continuing education, health, dental, life and disability insurance and a wellness program. As an employee-owned company, through the Employee Stock Ownership Plan, Schnabel employees directly benefit from the success of our growing firm.

Benefit options include:

• Medical insurance

• Dental insurance

• Flexible spending accounts

• Employee life & ADD insurance (100% company-paid)

• Short-term disability (100% company-paid)

• Long-term disability

• Supplemental life insurance

• 401(k) and profit-sharing plan

• Employee stock ownership plan (ESOP)

• Bonus program

• Paid time off

• 9 Paid Holidays

• Wellness program

• Professional development and tuition reimbursement

Job Description:

Our Jersey City, NJ office is seeking a Computational Water Resources Engineer to join our expanding Water Resources practice across the Northeast and the U.S. This position offers an exciting opportunity to apply advanced modeling, programming, and data analytics to challenging projects involving dams and reservoirs, river systems, flood risk and resiliency, hydrologic and hydraulic modeling, forecasting, and water resources management.

You will work alongside a multidisciplinary team of industry experts at the forefront of innovation, combining water resources engineering, computational modeling, geospatial and data analytics, and software development to solve complex problems and deliver impactful solutions for our clients.

We are looking for a curious, motivated, and technically driven professional who values attention to detail, continuous improvement, and collaboration. As an employee-owner, your voice will matter. You will have a say in how our business operates and will benefit from our financial success.

Job Responsibilities:

The candidate will serve as a Water Resources Engineer within Schnabel’s Water Engineering Practice, with a focus on computational modeling, forecasting, data analytics, and automation. Major focus areas for the role include:

• Develop, calibrate, validate, and apply hydrologic and hydraulic models to support flood hazard and climate risk assessments and the planning, design, and construction of water resources projects, including dams and reservoirs, levees, flood control, river restoration, resiliency, and climate adaptation efforts.

• Develop and apply river and reservoir system models to evaluate reservoir operations, flood management, water supply, hydropower, and alternative operating scenarios.

• Develop and implement hydrologic forecasting and decision-support tools, integrating observed and forecast hydrometeorological data with hydrologic, hydraulic, and reservoir models to support real-time and long-term water management decisions.

• Perform, review, and oversee complex water resources modeling studies, engineering analyses and design calculations, as well as the preparation of technical reports and presentations for mid- to large-scale projects.

• Develop, maintain, and enhance engineering automation tools, scripts, and computational workflows to improve the efficiency, consistency, scalability, and quality of hydrologic, hydraulic, consequence, and risk analyses.

• Design and implement data processing, model integration, model management, calibration, and post-processing solutions to support large-scale engineering analyses and reduce repetitive manual tasks.

• Apply programming, data analytics, statistical methods, optimization, and emerging technologies, including machine learning and AI-based approaches, where appropriate to enhance modeling, forecasting, automation, and engineering decision-making.

• Develop visualization and decision-support solutions that transform complex modeling results and large datasets into actionable information for engineers, clients, operators, and other stakeholders.

• Provide training, mentoring, and technical support to engineering staff on the use of computational tools, automated workflows, and best practices for engineering data management and modeling.

• Support project management activities including resource planning, work delegation, management of project budgets, invoicing, and backlog reporting.

• Contribute to maintaining and expanding Schnabel’s reputation in water engineering and computational modeling through technical innovation, published papers and white papers, collaboration with key partners and universities, and presentations at recognized conferences and workshops.

• Contribute to business development, marketing, proposal preparation efforts, and staff mentoring.

• Domestic and international travel, as necessary.

Required Skills/Experience:

• Bachelor’s degree in Civil Engineering, Water Resources Engineering, Environmental Engineering, Hydrology, Computational Science, or a related field. Master’s degree preferred.

• Professional Engineer (PE) license preferred.

• 5+ years of relevant experience in water resources engineering, hydrologic and hydraulic modeling, and computational water resources. Candidates outside this range who demonstrate strong technical capabilities and meet the core requirements may also be considered.

• Strong understanding of hydrologic and hydraulic modeling principles, with experience developing, calibrating, validating, and applying numerical models to complex water resources problems.

• Proficiency with industry-standard water resources and geospatial modeling tools such as HEC-HMS, HEC-RAS 1D/2D, HEC-SSP, RMC-BestFit, RMC-RFA, LifeSim, and ArcGIS Pro, or comparable platforms.

• Strong proficiency in Python programming for engineering analyses, data processing, model automation, visualization, and development of reproducible computational workflows; experience with JavaScript, C#, and C++ are a plus.

• Experience with HEC-RAS automation tools, including HEC-RAS Controller, batch simulations, model management, and/or automated post-processing of model results.

• Experience with GIS automation and scripting using tools such as ArcGIS Pro, ArcGIS ModelBuilder, ArcPy, GeoPandas, GDAL, or similar geospatial processing tools.

• Proficiency with engineering data management and analysis tools such as SQL, Pandas, Excel/VBA, Power BI, or related technologies.

• Familiarity with software development best practices including version control (e.g., Git), documentation, testing, and code review.

• Experience integrating engineering software through APIs, scripting interfaces, or custom automation tools.

• Effective time management, written communication skills, analytical skills, interpersonal skills, and the ability to work independently or as part of a team, efficiently balance multiple concurrent tasks, responsibilities, and commitments.

Other Requirements:

• Ability to pass a background check which may include criminal history, motor vehicle record, and credit check.

• Ability to pass a pre-employment drug screening.

The compensation range for this position is between $125,000 to $180,000. Compensation for this position may vary based on geographic location and other factors. We remain committed to providing competitive and equitable compensation to all employees, regardless of their location.

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities

This employer is required to notify all applicants of their rights pursuant to federal employment laws.

For further information, please review the Know Your Rights (https://www.eeoc.gov/poster) notice from the Department of Labor.