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Data Engineer - Onboarding

📅 Jul 30
Data EngineeringMachine LearningPythonSQL

📜 Description

  • Own the data ingestion layer for device telemetry, transaction events, and KYC signals, designing streaming and batch pipelines.
  • Build and evolve the feature platform for real-time and batch processing, ensuring feature correctness and observability.
  • Productionize fraud and identity ML models, implementing automated retraining and monitoring mechanisms.
  • Engineer KYC and AML risk signals from multi-vendor data sources, ensuring data quality and feature learnability.
  • Integrate new data sources and manage the warehouse and modeling layer in BigQuery.
  • Set technical direction, mentor team members, and document design decisions.

🛠️ Requirements

  • 8+ years of experience building production data and ML systems with ownership of both pipelines and models.
  • Deep proficiency in Python and strong SQL skills, with experience in distributed processing frameworks like Spark or Beam.
  • Hands-on experience with GCP or AWS cloud data stacks, including BigQuery, Dataflow, and Kubernetes.
  • Practical ML engineering experience with feature stores, model monitoring, and explainability.
  • Domain experience in fraud, risk, payments, or identity/KYC.

Benefits

  • Generous compensation in cash and equity.
  • Flexible paid time off and year-end break.
  • Health insurance
  • Dental
  • Vision coverage for employees and dependents
  • 4% matching in 401k / RRSP.
  • One-time stipend to set up a home office.
  • Monthly meal stipend.
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