150K–205K USD / year
Data Engineer - Onboarding
DataRemote — United States, Canada
Published on 2026-07-30
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About this role
Own the data and machine-learning pipelines that power Sardine’s onboarding, identity, and compliance decisions. This senior individual-contributor role spans data ingestion, feature engineering, model productionization, and production reliability.
About the company
Sardine is a financial crime platform that helps companies detect fraud, money laundering, and other risk with real-time behavioral and device intelligence.
Stack
PythonSQLApache BeamDataflowFlinkSparkAirflowCloud Composer
What you'll do
- Build and own streaming and batch ingestion pipelines for device, transaction, identity, and third-party data.
- Develop a feature platform with consistent streaming and batch computations and low-latency serving.
- Establish feature correctness, train/serve parity, reconciliation, and drift monitoring.
- Productionize fraud and identity models, including retraining, champion/challenger promotion, and rollback.
- Integrate KYC, AML, sanctions, identity, and enrichment signals into usable model features.
- Own BigQuery warehouse modeling, training datasets, and migration from dbt to scheduled SQL and Python pipelines.
- Design entity-resolution and graph data systems linking customers, devices, and financial identifiers.
- Set technical direction, write design documents, review work, and mentor engineers and data scientists.
What we're looking for
- 8+ years building production data and ML systems, with ownership of both pipelines and models.
- Strong Python and SQL, plus expertise in Spark, Beam, or Flink and streaming semantics.
- Experience with cloud data infrastructure; GCP is preferred.
- Practical ML engineering experience with feature pipelines, tree-based models, rare-event modeling, monitoring, and explainability.
- Experience with high-volume, low-latency feature serving.
- Fraud, risk, payments, lending, or identity/KYC domain experience, or ability to ramp up quickly in a regulated domain.
- Knowledge of data governance, PII protection, encryption, access control, and regional data residency.
- Strong written communication and comfort working independently amid ambiguity.
Nice to have
- Experience with customer-facing ML, model explainability for regulatory review, or shadow/challenger scoring.
- Experience at a high-growth B2B SaaS company or as an early data/ML hire.
Benefits
- Equity, with early exercise available for all options, including pre-vested options.
- Flexible paid time off and a year-end break.
- Health, dental, and vision coverage for employees and dependents in the US and Canada.
- 4% 401(k) or RRSP matching in the US and Canada.
- MacBook Pro and a one-time home-office setup stipend.
- Monthly meal and social meet-up stipends.
- Annual health and wellness and learning stipends.