Data Engineer - Onboarding
Tasks
- Apply encryption and PII governance
- Build feature platform
- Create partitioning and staging mart layers
- Design failover and caching for enrichment
- Enforce regional data residency in pipelines
- Enforce train serve parity
- Engineer entity resolution graphs
- Generate KYC AML identity risk features
- Implement champion challenger promotion
- Implement model rollback
- Integrate and harden third party data sources
- Mentor engineers and data scientists
- Migrate off dbt to SQL and Python pipelines
- Monitor feature drift
- Own BigQuery warehouse and modeling layer
- Own data ingestion pipelines
- Productionize model retraining and deployment
- Reconcile streaming and batch features
- Run recomputation tests against warehouse
- Screen sanctions PEP and adverse media
- Train fraud and identity models
- Write design docs and lead technical direction
Perks/Benefits
- 401k match or RRSP match
- Flexible paid time off
- Health and wellness stipend
- Health insurance dental and vision
- Home office stipend
- Learning stipend
- MacBook Pro
- Meal stipend
- Remote-first
- Social meet-up stipend
Skills/Tech-stack
Apache Airflow | Apache Beam | Apache Flink | At least once | BigQuery | Bigtable | Boosted Trees | CI/CD | CatBoost | Chronon | Cloud platform | Connected components | Data Governance | Data Modeling | Docker | Drift Detection | Entity Resolution | Exactly once | Feature Engineering | Feature Store | Flink | Google Cloud | Google Cloud Platform | Google Composer | Google Dataflow | Google Dataproc | Google Pubsub | Gradient Boosted Trees | Graph Data | Graph Data Modeling | Kubeflow | Kubernetes | Late data | LightGBM | Model Explainability | Model Monitoring | PII Encryption | Python | SHAP | SQL | Scikit-learn | Spark | Streaming processing | Terraform | Vertex AI | Watermarking | Windowing | XGBoost
Education
N/A
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