Sardine

Sardine

Data Engineer - Onboarding

North America

Sponsorship not specifiedDetected 1 day ago
PythonSQLBigQueryAWSGCPDockerKubernetesTerraformMachine Learningscikit-learnSparkAirflowdbtData Engineering

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Cap-exempt (no lottery)0
Sponsors this role52
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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About the role

  • Every onboarding decision we make - a payment approved, an account blocked, a KYC case escalated - is the output of a pipeline someone built.
  • This is a high-impact, highly technical IC role sitting at the intersection of data engineering and ML engineering.
  • You will write production code, make architectural calls that outlive your tenure, and raise the bar for how a small team ships fraud ML.

Responsibilities

  • Own the data ingestion layer that brings device telemetry, transaction events, KYC/identity signals, and third-party enrichment into the platform - designing streaming pipelines (Pub/Sub, Apache Beam on Dataflow, Flink) and batch pipelines (Python, Airflow on Cloud Composer, Spark on Dataproc) that are correct, observable, and cheap to extend.
  • Build and evolve our feature platform, where the same Chronon feature definitions are computed by Flink for streaming and Spark for batch, with aggregation windows from one hour to 300 days, served to the rules engine and to models under a sub-second budget.
  • Productionize fraud and identity ML models - training pipelines on Vertex AI and Kubeflow, gradient-boosted and tree-based models (XGBoost, LightGBM, CatBoost, scikit-learn), hyperparameter search, SHAP-based explanations, and score normalization - and build the automated retraining, champion/challenger promotion, and rollback machinery we don't yet have.
  • Engineer KYC, AML, and identity risk signals: document verification and doc-KYC outcomes, sanctions/PEP/adverse-media screening results, email and phone risk, synthetic identity indicators, bank and account verification, and periodic customer due diligence - turning noisy, multi-vendor, multi-jurisdiction data into features a model can actually learn from.
  • Own the warehouse and modeling layer in BigQuery - partitioning strategy, the staging-to-mart layer cake, training datasets, and the in-flight migration off dbt onto scheduled SQL and Python pipelines.
  • Set technical direction and raise the team's ceiling - write the design docs, run the reviews, mentor engineers and data scientists, and decide what we build versus buy.
  • You can explain a modeling tradeoff to a fraud analyst and a pipeline design to a backend engineer, and you write things down.
  • Much of this role is deciding what should exist, then building it.
  • Experience supporting customer-facing ML - bring-your-own-model integrations, model explainability for adverse action or regulatory review, or shadow/challenger scoring frameworks.

Requirements

  • Experience with high-volume, low-latency serving where a feature fetch has a few hundred milliseconds and there is no retry budget.
  • Domain experience in fraud, risk, payments, lending, or identity/KYC - or the demonstrated ability to get fluent in a regulated domain fast.
  • Comfort with data governance in a regulated environment: PII, encryption, access control, regional data residency, auditability.
  • Experience in high-growth B2B SaaS, or as an early data/ML hire who built the function rather than inherited it.
  • If you are seeking a meaningful career, you found the right place, and we would love to hear from you.

Nice to have

  • You have shipped models that made consequential automated decisions, not just dashboards.
  • Deep Python and strong SQL.
  • Hands-on experience with a modern cloud data stack: GCP strongly preferred (BigQuery, Dataflow, Dataproc, Pub/Sub, Bigtable, Composer, Vertex AI) or the AWS equivalents, plus Docker, Kubernetes, Terraform, and CI/CD.

Compensation

  • Generous compensation in cash and equity

Benefits

  • Generous compensation in cash and equity
  • Flexible paid time off and Year-end break
  • Health insurance, dental, and vision coverage for employees and dependents
  • One-time stipend to set up a home office - desk, chair, screen, etc.
  • Monthly meal stipend
  • Monthly social meet-up stipend
  • Annual health and wellness stipend
  • Annual Learning stipend
  • You understand why label latency, feedback loops, and adversarial drift make fraud modeling different from ordinary supervised learning.

Company info

  • Sardine is the leading agentic risk platform for fighting financial crime. Our integrated solution unifies data across risk teams to help organizations stop fraud in real time, prevent AI-driven attacks, and automate fraud and AML operations. Sardine's platform is strengthened by one of the fastest-growing fraud consortiums in the market, spanning more than 6 billion profiled devices, 800 million consumers, and 3 million businesses worldwide. Leading companies including FIS, GoDaddy, Intuit, Edward Jones, ZoomInfo, and Checkout.com rely on Sardine to secure and grow trust in their products.
  • Our culture:
  • We have hubs in the Bay Area, NYC, Austin, Toronto, and São Paulo. However, we maintain a remote-first work culture. #WorkFromAnywhere
  • We hire talented, self-motivated individuals with extreme ownership and high growth orientation.
  • Sardine is the leading agentic risk platform for fighting financial crime.
  • Our integrated solution unifies data across risk teams to help organizations stop fraud in real time, prevent AI-driven attacks, and automate fraud and AML operations.
  • Sardine's platform is strengthened by one of the fastest-growing fraud consortiums in the market, spanning more than 6 billion profiled devices, 800 million consumers, and 3 million businesses worldwide.
  • Leading companies including FIS, GoDaddy, Intuit, Edward Jones, ZoomInfo, and Checkout.com rely on Sardine to secure and grow trust in their products.
  • We value performance and not hours worked. We believe you shouldn't have to miss your family dinner, your kid's school play, friends get-together, or doctor's appointments for the sake of adhering to an arbitrary work schedule.
  • Remote - United States or Canada
  • From Home / Beach / Mountain / Cafe / Anywhere!
  • We are a remote-first company with a globally distributed team. You can find your productive zone and work from there.
  • About the role
  • We are looking for a Senior Data/ML Engineer to own the data and machine learning foundation that Sardine's compliance decisions run on.
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This listing is sourced directly from Sardine's careers page and normalized into a canonical job model.