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PrePass

Integrated weigh station bypass and toll management

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timePhoenix, AZ, USANo salary listed

About the Job

Requirements

  • Proven experience designing, building, and operating distributed data pipelines and cloud data platforms at scale.
  • Hands-on expertise in Test-Driven Development for data pipelines, including writing unit, integration, and data-contract tests before implementation, as well as pairing, refactoring, and continuous integration.
  • Practical experience integrating AI coding assistants and large language model-based tooling into daily engineering workflows to accelerate delivery, improve test coverage, and automate documentation.
  • Strong experience operating high-availability production systems with uptime, reliability, and observability expectations.
  • Experience driving engineering standards, architectural reviews, documentation, and mentorship within an Agile team.

Responsibilities

  • Design, build, and operate scalable ETL/ELT pipelines on Azure to ingest, transform, and integrate data from multiple sources; use advanced SQL, Apache Spark, and lakehouse technologies such as Databricks and Delta Lake to support analytics, reporting, and real-time operational workloads.
  • Partner with the team to define and execute a strategy for re-architecting legacy SQL Server Integration Services workloads into modern, cloud-native pipelines; lead proof-of-concept and prototyping work and produce clear recommendations.
  • Lead by example in writing clean, modular, maintainable code using strict Test-Driven Development, pair programming, continuous refactoring, and automated CI/CD pipelines.
  • Use AI-assisted development tools for code generation, automated unit and data-quality test creation, legacy refactoring, and pipeline anomaly detection.
  • Operate and monitor mission-critical data systems against service-level agreements for data freshness, uptime, and reliability; diagnose and resolve integration and data-quality failures, build end-to-end traceability and observability, and tune pipeline and compute performance for cost and scalability.
  • Define and evolve team-wide data engineering standards, architectural documentation, and continuous-improvement initiatives within an Agile environment.

Desired Qualifications

  • Experience in Data Science or Machine Learning, particularly MLOps, model deployment, Feature Store management, or feature engineering on Databricks.
  • Experience with Infrastructure as Code, such as Terraform or Bicep, for managing Databricks workspaces and cloud resources.
  • Familiarity with event-driven architecture, including queues, batches, and pub/sub models.
  • Production experience with the Databricks platform, including Delta Lake, PySpark/Spark SQL, Databricks Workflows, and Unity Catalog.
  • Background in high-volume IoT, telematics, or transportation industry data.

About the Company

PrePass

Integrated weigh station bypass and toll management

PrePass helps North American commercial fleets by providing integrated weigh station bypass, electronic toll management, and compliance solutions. It uses GPS and a mobile app to connect bypass decisions with safety screening and toll data, so fleets can save time, lower costs, improve safety scores, and boost driver productivity. The system works by linking weigh station data, safety screening results, toll transactions, and fleet information into one ecosystem that supports real-time decisions and easier compliance. PrePass differentiates itself through a large, established network (100,000+ fleets and 800,000+ vehicles), a nonprofit public-private governance model via the PrePass Safety Alliance, and a seamless combination of bypass, safety screening, toll management, and actionable data for fleets and enforcement partners. The goal is to improve highway safety and efficiency while helping fleets stay compliant and competitive.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Phoenix, AZ
Founded
1993

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