
51 - 200 employés
💼 Conseil
🏥 Santé
📦 Logistique
Consulting • Healthcare • Logistics
Oteemo Inc. est une entreprise de conseil en technologie spécialisée dans la transformation DevSecOps, la modernisation des infrastructures et les solutions de cybersécurité. L'entreprise aide les entreprises à déployer rapidement des capacités numériques sans compromettre la sécurité et la qualité. Oteemo exploite l'intelligence artificielle, adopte les méthodologies Agile et fournit des services de transformation des affaires. Elle dessert divers secteurs, notamment les services financiers, la santé, la technologie et le gouvernement, en modernisant les opérations, en renforçant la sécurité et en stimulant l'innovation. Oteemo opère depuis plusieurs sites, notamment aux États-Unis, au Mexique et en Inde, en fournissant des solutions dirigées par des experts pour améliorer l'efficacité, la sécurité et la fiabilité.
🕒 il y a 23 jours
🗣️🇺🇸🇬🇧 Anglais requis
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51 - 200 employés
💼 Conseil
🏥 Santé
📦 Logistique
Consulting • Healthcare • Logistics
Oteemo Inc. est une entreprise de conseil en technologie spécialisée dans la transformation DevSecOps, la modernisation des infrastructures et les solutions de cybersécurité. L'entreprise aide les entreprises à déployer rapidement des capacités numériques sans compromettre la sécurité et la qualité. Oteemo exploite l'intelligence artificielle, adopte les méthodologies Agile et fournit des services de transformation des affaires. Elle dessert divers secteurs, notamment les services financiers, la santé, la technologie et le gouvernement, en modernisant les opérations, en renforçant la sécurité et en stimulant l'innovation. Oteemo opère depuis plusieurs sites, notamment aux États-Unis, au Mexique et en Inde, en fournissant des solutions dirigées par des experts pour améliorer l'efficacité, la sécurité et la fiabilité.
• Design, model, and implement graph data structures that capture complex system relationships, workflows, and time-dependent processes using Neo4j, Gremlin, or similar tools. • Build and integrate web application back ends and contribute to front-end development as needed to deliver complete, production-ready features. • Develop and maintain robust ETL and data pipelines spanning structured, semi-structured, and unstructured data, with strong attention to data quality. • Engineer real-time and event-streaming workflows that handle high-velocity, sequential data flows. • Deploy and operate enterprise applications in cloud environments using containerization and orchestration, applying DevOps, DataOps, and MLOps practices. • Apply GenAI/ML techniques, including GraphRAG, to graph-related and NoSQL data problems. • Write thorough unit, integration, and API tests to ensure robust, scalable, and maintainable solutions. • Run simulations and apply advanced analytics in Python to solve complex mission problems. • Align data engineering approaches with large-scale interconnected systems to ensure adaptability and scalability.
• Advanced degree in a quantitative field (e.g., computer science, machine learning, applied statistics, or mathematics) or equivalent experience, with 7–8 years of relevant experience. • Active Secret/TS/SCI clearance (or SCI-eligibility), ideally with past or current DoD SAP/SAR access. • Proven experience with graph databases and analytics, including Neo4j, Gremlin, or similar tools, and query languages like Cypher or Gremlin; ability to model complex system relationships, workflows, and time-dependent processes. • Strong programming skills in modern languages such as Python, Java, JavaScript/TypeScript, or Go, with expertise in writing clean, maintainable, and scalable code. • Experience building and integrating web application back ends and contributing to front-end development when needed. • Extensive experience with data engineering and pipelines, including ETL, data quality, and working across structured, semi-structured, and unstructured data; familiarity with event streaming, real-time data processing, and high-velocity sequential data flows. • Practical knowledge of software engineering best practices, including DevOps, DataOps, MLOps, containerization (e.g., Docker), and orchestration. • Experience with distributed computing frameworks and cloud platforms, with a focus on deploying enterprise applications in cloud environments. • Strong testing skills, including unit testing, integration/API testing, and ensuring robust, scalable solutions. • Experience with NoSQL databases and working with graph-related problems, including the use of GenAI/ML techniques like GraphRAG. • Proven ability to align data engineering approaches with large-scale interconnected systems, ensuring adaptability and scalability.
• Ability to make a noticeable difference for the organization and our customers • Tremendous growth opportunity by becoming part of a rapidly growing organization. • Competitive pay and benefits
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