Data Platform Engineer

Worth AI, a leader in the computer software industry, is looking for a talented and experienced Data Platform Engineer to join their innovative team. At Worth AI, we are on a mission to revolutionize decision-making with the power of artificial intelligence while fostering an environment of collaboration, and adaptability, aiming to make a meaningful impact in the tech landscape.. Our team values include extreme ownership, one team and creating reaving fans both for our employees and customers. As a Data Platform Engineer, you will design, build, and operate the core data services that power our products and analytics. You’ll own end-to-end data pipelines and API services that ingest, process, and expose high-quality data to internal customers (data science, analytics, product, and other engineering teams) and external partners. You’ll be part of a small, high-impact team that treats the data platform as a product with strong SLAs, and reliable self-service for internal and external users. Responsibilities What you’ll do: - 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 ** All Remote Hires - will be required to travel to Orlando, Florida at least twice per year for Town Halls and team collaboration in addition to orientation in Orlando, Florida 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