Data Platform Engineer

🔥 0 minutes ago

🐊 Florida – Remote

🐊 Florida – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🏗️ Platform Engineer

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Worth AI

WebsiteLinkedInAll Job Openings

11 - 50 employees

🤖 Artificial Intelligence

💳 Fintech

🏦 Banking

Artificial Intelligence • Fintech • Banking

Worth AI is a company that specializes in enhancing financial security and risk management through advanced AI-driven solutions. Their platform offers a suite of tools designed for seamless onboarding, compliance, and credit risk assessment. They help banks, fintech companies, and credit unions streamline operations by automating processes such as KYC/KYB compliance, reputation monitoring, and automated credit underwriting. Worth AI's technology provides real-time risk monitoring, predictive analytics, and AI-generated insights to improve decision-making, safeguard institutions, and boost revenue. Key offerings include Worth Score™, an AI-driven credit score solution, and unique AI underwriting systems that enhance the accuracy and efficiency of financial assessments.

📋 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

🎯 Requirements

• 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

🏖️ Benefits

• 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