Consultant, Enterprise Data Integration Architect

Overview

Vantive is a vital organ therapy company on a mission to extend lives and expand possibilities for patients and care teams everywhere. For 70 years, our team has driven meaningful innovations in kidney care. As we build on our legacy, we are deepening our commitment to elevating the dialysis experience through digital solutions and advanced services, while looking beyond kidney care and investing in transforming vital organ therapies.

Greater flexibility and efficiency in therapy administration for care teams, and longer, fuller lives for patients— that is what Vantive aspires to deliver.

We believe Vantive will not only build our leadership in the kidney care space, it will also offer meaningful work to those who join us. At Vantive, you will become part of a community of people who are focused, courageous and don’t settle for the mediocre. Each of us is driven to help improve patients’ lives worldwide. Join us in advancing our mission to extend lives and expand possibilities.

We are seeking a visionary and hands-on Enterprise Data Integration Architect to join our Integration Architecture team and serve as the dedicated integration representative to partner with the Data & AI organization. This role is pivotal in shaping and executing our enterprise-wide integration strategy for data and AI initiatives, leveraging cutting-edge technologies and cloud-native platforms on AWS and/or Azure. The ideal candidate will have deep experience in designing and implementing scalable, secure, and high-performance integration architectures in partnership with the Enterprise Data Solution Architects to enable advanced analytics, machine learning, and AI capabilities.

You will collaborate closely with data architects, data engineers, data scientists, and enterprise architects to ensure seamless data flow across systems, domains, and platforms.

Strategic Leadership

• Define and drive the integration strategy for data and AI initiatives across the enterprise
• Partner with Data & AI leadership to align integration architecture with business goals and data strategies
• Evaluate and recommend modern integration technologies and patterns (e.g., event-driven, API-led, streaming, data mesh)
• Partner with regional teams in defining and designing integration patterns and architectures

Architecture & Design

• Design scalable, secure, and resilient integration architectures on AWS and/or Azure using services such as Glue, Lambda, Kinesis, S3, Redshift, and others
• Develop integration patterns for real-time, batch, and near-real-time data movement across cloud and hybrid environments
• Ensure data lineage, governance, and observability are embedded in integration designs

Collaboration & Enablement

• Act as the primary liaison between the Integration and Data/AI teams, ensuring alignment and shared understanding
• Mentor and guide integration developers on best practices
• Collaborate with enterprise architects to ensure consistency across platforms and domains

Innovation & Continuous Improvement

• Stay abreast of emerging trends in data integration, AI, and cloud technologies
• Lead proof-of-concept initiatives to evaluate new tools and methodologies
• Contribute to the development of reusable integration assets and frameworks

Required Skills

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field
• 10 or more years of experience in enterprise integration architecture, with at least 3 years focused on data-centric integrations
• Proven experience with AWS data and integration services (Examples: Glue, Kinesis, Lambda, Event Bridge, S3, Redshift, or etc.)
• Hands-on experience building or enabling AI agents in production or advanced POCs
• Experience with agent frameworks and orchestration patterns
• Understanding of MCP
• Experience integrating LLMs via APIs for enterprise use cases
• Familiarity with RAG architectures, Vector database and embeddings, prompt management, tool calling, and agent workflows
• Exposure to Azure cloud services will be a plus
• Exposure to modern data architectures (e.g., data lakehouse, data mesh, real-time streaming)
• Experience with integration platforms such as Mule Soft, Apache Kafka,…