PrePass
PrePass
PrePass nodrošina tehnoloģijās balstītus pakalpojumus komerciālajiem autoparkiem visā Ziemeļamerikā, tostarp iespēju apbraukt transportlīdzekļu svēršanas stacijas un elektroniski apmaksāt ceļu nodevas. Uzņēmuma risinājumi palīdz privāto autoparku pārvaldītājiem, pārvadātājiem, kas strādā pēc pasūtījuma, un īpašniekiem-operatoriem vienkāršot atbilstību uz ceļiem un ceļu nodevu administrēšanu, kā arī uzlabot darbības pārskatāmību. Uzņēmums apvieno plašu apbraukšanas tīklu, vairākas tehnoloģiju iespējas un klientu atbalstu, lai palīdzētu transporta uzņēmumiem pārvaldīt autoparka efektivitāti, degvielas patēriņu, drošību un riskus. PrePass, kas dibināts 1995. gadā, darbojas loģistikas, transporta un konsultāciju nozarēs, un tajā strādā aptuveni 201–500 darbinieku.

Senior Data Engineer

Lead the design and growth of PrePass’s Azure data platform, building dependable pipelines with Databricks and Delta Lake. Support analytics and real-time operations for transportation and toll-management services.

Apraksts

  • Design and expand PrePass’s core data platform.
  • Build and operate scalable Azure ETL/ELT pipelines that combine data from multiple sources.
  • Apply SQL, Apache Spark, Databricks, and Delta Lake to analytics, reporting, and real-time workloads.
  • Plan and deliver modernization of legacy SSIS workloads.
  • Lead proofs of concept and prototypes, then recommend next steps.
  • Promote test-driven development, pair programming, continuous refactoring, and automated CI/CD.
  • Apply AI-assisted tools to code generation, test creation, legacy refactoring, and pipeline anomaly detection.
  • Monitor critical data systems against freshness, uptime, and reliability SLAs.
  • Investigate and fix data integration and quality issues.
  • Establish end-to-end traceability and observability.
  • Optimize pipelines and compute for cost and scale.
  • Set and maintain data engineering standards and architecture documentation.
  • Drive ongoing improvements within an Agile team.
  • Mentor other engineers.

Prasības

  • Demonstrated experience designing, building, and operating distributed data pipelines and cloud data platforms at scale.
  • Practical TDD experience for data pipelines, including unit, integration, and data-contract testing.
  • Experience with XP practices such as pairing, refactoring, and continuous integration.
  • Experience incorporating AI coding assistants and LLM-based tools into engineering workflows.
  • Experience operating highly available production systems with uptime, reliability, and observability expectations.
  • Experience setting engineering standards, conducting architecture reviews, documenting systems, and mentoring within an Agile team.
  • Experience in data science or machine learning, especially MLOps, model deployment, Feature Store management, or feature engineering on Databricks.
  • Experience with infrastructure as code tools such as Terraform or Bicep.
  • Familiarity with event-driven architectures, including queues, batches, and publish/subscribe models.
  • Production experience with Databricks, Delta Lake, PySpark or Spark SQL, Databricks Workflows, and Unity Catalog.
  • Experience working with high-volume IoT, telematics, or transportation data.

Priekšrocības

  • Medical, dental, and vision coverage begins on the hire date.
  • Paid time off includes vacation, sick leave, holidays, and floating holidays.
  • 401(k) plan with an employer match.
  • Company-funded lifestyle account for physical and mental well-being expenses.
  • Tuition reimbursement program.
  • Optional benefits include legal and pet discounts.
  • Employee Assistance Program at no cost.
  • Company-sponsored Culture Team supporting physical, mental, and professional well-being.
  • Community giving initiatives.
  • Employee development programs.

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