About the RoleWe are building an AI-native data platform that powers fraud detection and response across 360 Fraud Protection. We are hiring a Staff or Principal Data Engineer to own the data platform and data lake at the heart of that work. You work hands-on and own the domain end-to-end, alongside a small group of senior engineers, data scientists and product partners.
- Owns the unified data platform and data lake that powers detection and response across 360 Fraud Protection.
- Every detection model and downstream AI capability depends on this data foundation, which makes it one of the highest-leverage engineering roles on the team.
- Stronger, broader and more reliable fraud signal directly improves detection accuracy, reduces customer losses and protects brand trust.
Key Responsibilities- Own the design, build and operation of the data lake and ingestion platform end-to-end, from architecture through production reliability.
- Build low-latency batch and streaming pipelines that ingest signals from internal and external sources, normalize them to a common schema, enrich them with context and serve model-ready data to the layers above.
- Make adding a new data source a routine task rather than a project, so our view of risk keeps widening over time.
- Establish data quality, freshness, completeness, lineage and observability so the platform is trustworthy enough to automate on top of.
- Build data pipelines that ground generative AI, including unstructured text and threat intelligence processing, embedding generation, vector storage and retrieval.
- Own deployment, CI/CD and operational reliability of the platform on Kubernetes.
- Partner with data science, product and architecture to turn the platform into a shared foundation across 360 Fraud Protection.
Required Qualifications- Extensive experience building and operating large-scale data platforms and data lakes, with comfort working at high data volumes.
- Deep, hands-on expertise with Apache Spark, Apache Flink and modern big-data systems.
- Proven command of best practices for building and maintaining data pipelines in both batch and streaming modes.
- Strong production engineering skills across the full delivery lifecycle, including Kubernetes and CI/CD tooling, with the ability to ship end-to-end.
- A track record of owning data infrastructure end-to-end with limited supervision.
Preferred Qualifications- Experience with generative AI and embedding models, including embedding pipelines, vector databases and retrieval.
- A cybersecurity or threat intelligence background, with hands-on exposure to threat types such as phishing, mobile threats and malware.
- Familiarity with transaction data and transaction fraud signals.
Compensation - Base salary range: $180 - $270
- Bonus / commission: 15%
Travel- Minimal travel expected. This is an on-site role based in New York City, with 3-4 days per week in the office.
