Data Platform Engineer

🕒 il y a 1 mois

🐊 Florida – Distant

🐊 Florida – Remote

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

🚰 Ingénieur Data

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Worth AI

Site WebLinkedInTous les Emplois

11 - 50 employés

💼 Conseil

🛡️ Assurance

🤖 Intelligence artificielle

Consulting • Insurance • Artificial Intelligence

Worth AI est une entreprise spécialisée dans l'amélioration de la sécurité financière et de la gestion des risques grâce à des solutions avancées basées sur l'intelligence artificielle. Leur plateforme offre un ensemble d'outils conçus pour une intégration fluide, la conformité et l'évaluation des risques de crédit. Ils aident les banques, les entreprises fintech et les coopératives de crédit à rationaliser leurs opérations en automatisant des processus comme la conformité KYC/KYB, la surveillance de la réputation et la souscription de crédits automatisée. La technologie de Worth AI fournit une surveillance des risques en temps réel, des analyses prédictives et des insights générés par l'IA pour améliorer la prise de décision, protéger les institutions et augmenter les revenus. Les offres clés incluent Worth Score™, une solution de score de crédit basée sur l'IA, et des systèmes uniques de souscription par IA qui améliorent la précision et l'efficacité des évaluations financières.

Description

• Architect and implement entity resolution logic to de-duplicate and link disparate data points into unified "Golden Records" for businesses and individuals • Design and maintain a high-performance global business knowledge graph and ontology to map complex ownership chains, UBOs, and hidden risk relationships across international borders • Implement a hybrid storage strategy that bridges graph databases for relationship mapping with document and search stores for rich metadata and adverse media content • Optimize the platform for real-time risk assessment, ensuring the ability to traverse multiple levels of ownership in milliseconds to support automated "Go/No-Go" onboarding decisions • Design and build scalable data services and APIs for ingesting, transforming, and serving data across the company • Develop and maintain batch and streaming data pipelines using modern data processing frameworks and AWS cloud-native tooling • Own the reliability, performance, and API first data platform, including monitoring, alerting, and on-call where appropriate • Implement best practices for data modeling, quality, lineage, and governance to ensure trustworthy, well-documented datasets • Work closely with data scientists, analysts, and application engineers to understand their needs and translate them into robust platform capabilities • Drive automation and standardization through CI/CD, model as a service, and reproducible environments • Help define and evolve the architecture of our data platform as a true internal service with clear contracts, SLAs, and versioned APIs

🎯 Exigences

• Expertise in Graph Ecosystems: Hands-on experience with Graph databases (e.g., Neo4j, AWS Neptune, or TigerGraph) and query languages like Cypher or Gremlin • Identity & Linkage Mastery: Proven experience with Entity Resolution or Record Linkage (e.g., using tools like Senzing, Quantexa, or custom probabilistic matching models) • Schema Design: Ability to design flexible ontologies that handle evolving regulatory data (e.g., changing PEP definitions or Sanction list formats) • API Performance for Graphs: Experience building GraphQL or REST APIs specifically optimized for graph traversals and deep-tree lookups • Experience building centralized data platforms or “data-as-a-service” offerings at scale (e.g., at a large tech or cloud-native company) • Strong software engineering skills in at least one language commonly used for data and services (e.g., Python, Java, Go, Rust) • Hands-on experience building data pipelines and ETL/ELT workflows on a major cloud provider (AWS preferred) • Experience with modern data stack tools such as Spark/Flink, Kafka/Kinesis, Airflow/managed schedulers, and data warehouses (e.g., Snowflake, Redshift, BigQuery, Databricks) • Familiarity with DevOps practices: CI/CD, containerization (Docker), orchestration (Kubernetes), and infrastructure-as-code (Terraform) • Strong focus on observability (metrics, logs, traces), resilience, and building early warning signals • Comfort collaborating cross-functionally and communicating clearly with both technical and non-technical stakeholders. • **Nice to Have** • Background supporting machine learning or real-time decisioning use cases from a platform point of view • Compliance Domain Knowledge: Understanding of AML, CTF, and KYC/KYB data structures (e.g., LEIs, ISO 20022) • Geospatial Data: Experience handling global address normalization and geospatial indexing for risk detection

🏖️ Avantages

• Health Care Plan (Medical, Dental & Vision) • Retirement Plan (401k, IRA) • Life Insurance • Flexible Paid Time Off • 9 paid Holidays • Family Leave • Work From Home • Free Food & Snacks (Orlando) • Wellness Resources