• Lead and develop a team of engineers, ranging from graduate to senior • Oversee commercial engagements and support timely delivery on agreed project milestones • Participate as technical lead on complex customer engagements involving complete system architectures • Implement disciplined engineering processes • Integrate and maintain platform-oriented software stacks • Optimize Ubuntu for latest hardware platforms • Display technical leadership internally and within our external communities • Contribute to code reviews and technical documentation • Be an active part of the leadership team, collaborating with other leaders

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

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

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