Senior Data Engineer
Design, build, and operate CDC pipelines using Debezium to capture changes from source databases. Stream and route data through Kafka or Azure Event Hubs while ensuring reliability and low latency.
Design, build, and operate CDC pipelines using Debezium to capture changes from source databases. Stream and route data through Kafka or Azure Event Hubs while ensuring reliability and low latency.
The Engineering Manager will lead a high-impact team focused on internal developer platform initiatives and developer productivity. This role involves active contribution to architecture, coding, and technical decision-making while managing team performance and roadmap execution.
The engineer will translate AI architectures into secure, scalable, and maintainable production systems using LangChain and LangGraph. They will build and deploy LLM-powered applications, agentic workflows, and RAG solutions while ensuring operational readiness and performance.
The Principal Software Engineer will lead the visual modernization of an existing application by migrating legacy jQuery pages to a modern Vue-based architecture. This role involves hands-on coding, performance optimization, and leveraging AI-assisted development tools to maintain high-quality, scalable interfaces.
The Principal Software Engineer will lead the visual modernization of an existing Vue and PHP application to improve user experience and interface quality. This role involves hands-on coding, implementing AI-assisted development workflows, and collaborating with product and UX teams to deliver performant, accessible UI improvements.
You will design and build scalable data engineering solutions while developing a framework that centralizes ETL logic and metric definitions. Additionally, you will collaborate with cross-functional teams to create self-service data tools and support data-driven decision-making.
Design, build, and maintain CI/CD pipelines while automating infrastructure provisioning and management using Infrastructure as Code. Collaborate with cross-functional teams to optimize deployment reliability, observability, and operational efficiency across cloud-native environments.
Lead end-to-end delivery of technology projects by coordinating cross-functional teams and managing project scope, timelines, and budgets. Facilitate Agile ceremonies and ensure alignment between business objectives and technical execution while maintaining compliance and quality standards.
The Data Engineer will design and implement robust data models and platforms to support healthcare analytics and AI initiatives. They will collaborate with cross-functional teams to gather requirements, ensure data quality, and integrate heterogeneous data sources.
Design, build, and deploy scalable backend services and data pipelines using Python on Google Cloud Platform. Maintain existing Java services while integrating AI/LLM capabilities into backend applications.
The Project Manager will lead end-to-end delivery of technology initiatives within the healthcare sector by coordinating cross-functional teams. They are responsible for managing project timelines, budgets, risks, and dependencies while ensuring alignment with business objectives.
Design, develop, and maintain high-quality native iOS applications using Swift while collaborating with backend and web teams. Participate in architecture decisions, code reviews, and the troubleshooting of application performance and stability issues.
Design, develop, and maintain high-quality native Android applications using Kotlin and Android Studio. Collaborate with backend and web engineering teams to ensure reliable API integrations and a consistent user experience.
Develop and enhance Databricks pipelines while managing business-critical data and collaborating with stakeholders. Design and implement data models to support machine learning, AI, and ad-hoc access to large datasets.
Design and implement scalable data engineering solutions within the Microsoft Azure and Databricks ecosystem. Provide technical leadership and mentorship to engineering teams while establishing standards for performance, reliability, and data governance.
Design and implement scalable data engineering solutions within the Microsoft Azure and Databricks ecosystem. Provide technical leadership and mentorship to engineering teams while establishing standards for data platform performance and reliability.
Design and implement scalable data engineering solutions within the Microsoft Azure and Databricks ecosystem. Provide technical leadership and mentorship to the engineering team while establishing best practices for data platform performance and reliability.
Design, develop, and maintain scalable data pipelines and models within a Microsoft Azure and Databricks environment. Collaborate with engineering teams to implement data platform solutions while ensuring data quality and performance optimization.
Design and implement scalable data engineering solutions within the Microsoft Azure and Databricks ecosystem. Provide technical leadership and mentorship to the data engineering team while ensuring high standards for data architecture and security.
Design, develop, and maintain scalable data pipelines and models using Microsoft Azure and Databricks. Collaborate with engineering teams to integrate enterprise data sources and optimize data processing workflows for performance and reliability.
You will work directly with customers to design, build, and deploy production-grade AI solutions using LLMs and agentic technologies. Additionally, you will act as a technical bridge between customer needs and internal product teams to influence engineering roadmaps.
Lead the design, architecture, and maintenance of enterprise and domain data models to support strategic data transformation. Facilitate cross-functional alignment between business and technical teams to establish unified data structures and governance practices.
Design, build, and maintain scalable data pipelines using Databricks while managing CI/CD workflows via Azure Pipelines. Optimize ETL/ELT processes for performance and collaborate with stakeholders to define data requirements and ensure data quality.
You will work directly with customers to design, build, and deploy production-grade AI-powered solutions using LLMs and agentic technologies. Additionally, you will act as the technical voice of the customer to influence product roadmaps and mentor other engineers.
You will work directly with customers to design, build, and deploy production-grade AI solutions using LLMs and agentic technologies. Additionally, you will act as a technical owner to translate business requirements into scalable systems while providing feedback to internal product and engineering teams.
Translate approved AI architectures into secure, scalable, and production-ready applications using LangChain and LangGraph. Build and deploy LLM-powered assistants, RAG pipelines, and agentic workflows while ensuring operational readiness and performance.
Translate approved AI architectures into secure, scalable, and maintainable production-ready systems using LangChain and LangGraph. Build and deploy LLM-powered applications, agentic workflows, and RAG solutions while ensuring operational readiness and performance.
Design, build, and deploy scalable backend services and data pipelines using Python and Java on Google Cloud Platform. Integrate AI/LLM capabilities into applications while maintaining high security and code quality standards.
You will play a key role in designing, developing, and maintaining robust backend systems that power the company's AI-driven applications. You will collaborate with the engineering team to ensure high-quality code and scalable architecture.
Drive new business generation within enterprise-level retail and logistics companies. Build and manage a high-value sales pipeline through strategic prospecting and executive networking to meet senior-level quotas.