A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.
As a seasoned Solution Architect specializing in Data Platforms, you design end-to-end Big Data Solutions across various platforms, leveraging your extensive experience in managing large data repositories. You possess a deep understanding of industry standards, best practices, and key technologies such as the HADOOP Framework and Cloud native platforms. Your primary responsibilities will include: • Design End-to-End Solutions: Create tailored data solutions for clients, utilizing Cloud and traditional data platform offerings, and oversee the architecture for data platform and cognitive components. • Develop Data Strategies: Leverage expertise in managing large data repositories to develop effective data management strategies, incorporating industry standards and best practices. • Oversee Architecture: Guide the architecture for data platform and cognitive components, including unstructured data technologies, annotation, and related data and analytics. • Collaborate with Clients: Work closely with clients to understand their needs and deliver customized data solutions that meet their requirements. • Drive Technical Excellence: Stay up-to-date with emerging trends and technologies, applying deep expertise in data platforms to drive technical excellence and innovation.
* Proven experience designing and delivering end‑to‑end Big Data solutions across multiple platforms
* Extensive experience managing large‑scale data repositories (terabyte scale or larger)
Cloud & Cloud‑Native Expertise
* Strong experience with one or more cloud platforms: AWS, Azure, Google Cloud, IBM Cloud
* Experience with cloud‑native data platforms such as Snowflake
* Solid understanding of containerized data platforms and data on OpenShift
Hadoop & Big Data Ecosystem
* Deep expertise in the Hadoop framework, ecosystem, and MapReduce concepts
* Strong understanding of distributed data processing patterns and architectures
Streaming & Kafka
* Hands‑on experience designing and operating Kafka‑based data streaming platforms
* Strong understanding of Kafka components including:
* Topics, partitions, replication
* Access Controls (ACLs)
* Zookeeper
* Schema Registry
* Familiarity with Confluent Kafka is required
Software Engineering & APIs
* Strong hands‑on experience with Java and Spring Boot
* Experience building and consuming RESTful APIs
* Ability to write comprehensive unit and integration tests
Microservices & CNCF
* Solid understanding of microservices architecture and design principles
* Strong knowledge of CNCF concepts, containers, Docker, and Kubernetes fundamentals
DevOps & CI/CD
* Practical experience with CI/CD pipelines, containerization, and automated deployments
* Ability to troubleshoot performance, data flow, and operational issues in production systems
Delivery & Ways of Working
* Experience working in Agile delivery environments
* Strong collaboration, communication, and technical leadership skills
Cloud Native Platform Expertise: Experience with Cloud native platforms such as AWS, Azure, Google, IBM Cloud, or Cloud Native data platforms like Snowflake, with the ability to leverage these platforms to create tailored data solutions.
• HADOOP Framework Knowledge: Deep understanding of the HADOOP Framework, Ecosystem, MapReduce, and Data on Containers (data in OpenShift), with the ability to apply this knowledge to design end-to-end Big Data Solutions.
• Unstructured Data Technology Understanding: Strong understanding of unstructured data technologies, annotation, and related data and analytics, with the ability to guide the architecture for data platform and cognitive components.
* Experience with enterprise integration and industry frameworks, including BIAN (preferred)
* Prior experience supporting production systems and participating in operational / on‑call rotation
* Exposure to:
* Data governance, metadata management, and data quality frameworks
* AI/ML data pipelines and cognitive analytics enablement
* Experience working with financial services, regulated industries, or large enterprise platforms
* Consulting or client‑facing experience with the ability to present architecture and technical trade‑offs clearly