Principal Data Engineer
Core
Design and evolve the petabyte-scale data platform powering real-time AML/KYC and Fraud products, serving billions of signals daily for global financial crime detection.
Role type
Principal Data Engineer (Strategy & Architecture)
Builds
Petabyte-scale data platforms, real-time knowledge graphs, ingestion frameworks, event buses, and feature stores for AI/ML teams.
Domain
Financial Services / RegTech / Real-time Data Infrastructure
Deliverable
production ML models | infrastructure
Required skills
Distributed data systems architecture, streaming (Kafka), batch/ELT (Spark, Flink, dbt), cloud infrastructure (AWS, GCP), containerization (Kubernetes, Docker), Python, data quality & observability, technical leadership, cross-team collaboration.
Preferred skills
Financial services domain knowledge (AML, KYC, fraud), knowledge graph & entity resolution, ML/LLM workload support, external technical representation.
Technologies
Kafka, Spark, Flink, dbt, Airflow, Argo Workflows, Postgres, Yugabyte, Kubernetes, Docker, ArgoCD, Grafana Cloud, gRPC, Python, Kotlin, TypeScript, React, AWS, GCP.
Responsibilities
Set medium-to-long term technical direction for the data domain; lead architectural design of complex, business-critical data systems spanning multiple tribes; shape engineering ways of working including data quality standards and tooling; tackle hardest data problems with direct company impact; coach engineers across the organization; represent the company at industry events.
Seniority
Principal, strategy & mentorship