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