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Data Engineer - Onboarding

Summary

Build and own data pipelines, feature stores, and ML models for fraud/identity compliance at a fintech company using Python, SQL, Spark, and GCP.

You will own the data and machine learning foundation for compliance decisions. You will build ingestion and feature pipelines, productionize fraud and identity models, engineer KYC and AML signals, manage warehouse and entity-resolution systems, enforce data governance, and set technical direction while mentoring engineers and data scientists.

Responsibilities

  • Own the data ingestion layer for device, transaction, KYC, identity, and enrichment data
  • Build streaming and batch data pipelines
  • Build and evolve the feature platform
  • Establish feature correctness and monitoring practices
  • Productionize fraud and identity machine learning models
  • Engineer KYC, AML, and identity risk signals
  • Integrate and harden third-party data sources
  • Own the BigQuery warehouse and modeling layer
  • Design entity-resolution and graph data systems
  • Enforce encryption, data residency, PII handling, and feature gating
  • Set technical direction, write design documents, run reviews, and mentor engineers and data scientists

Requirements

  • 8+ years building production data and machine learning systems
  • Deep Python and strong SQL
  • Experience with Spark, Beam, or Flink
  • Experience with GCP or equivalent AWS services
  • Experience with Docker, Kubernetes, Terraform, and CI/CD
  • Experience with feature stores and feature pipelines
  • Experience with gradient-boosted tree models
  • Experience with model monitoring, drift detection, and explainability
  • Experience with high-volume, low-latency serving
  • Experience in fraud, risk, payments, lending, or identity/KYC
  • Experience with data governance, PII, encryption, access control, and auditability
  • Strong written communication

Benefits

  • Equity
  • Early exercise for all options including pre-vested options
  • Remote work
  • Flexible paid time off
  • Year-end break
  • Health insurance
  • Dental insurance
  • Vision coverage
  • 401k/RRSP matching
  • MacBook Pro
  • Home office setup stipend
  • Monthly meal stipend
  • Monthly social meet-up stipend
  • Annual health and wellness stipend
  • Annual learning stipend

See also

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