Enterprise Solution Architect

CapgeminiVan Buren Township, IN

About The Position

We are seeking an experienced Enterprise Solution Architect with a strong background in software development, cloud, and big data solutions. The ideal candidate will have a proven track record in architecting large-scale distributed data processing and warehousing systems, with a focus on cloud-native and Big Data/MPP solutions. This role involves setting technology direction, defining future state architectures and roadmaps, and leading efforts to ensure alignment with architectural guidelines. You will collaborate with business units to develop cohesive solutions, engage in senior-level technology discussions, and mentor development teams on architecture best practices. The role requires a proactive individual with excellent leadership, communication, and problem-solving skills, capable of driving innovation and adoption of new technologies, including GenAI and LLMs.

Requirements

  • 15+ years of software development experience building large scale distributed data processing & Warehousing systems/applications.
  • Experience of at least 3 years in architecting Cloud (in any cloud) + Big Data or MPP solutions at enterprise scale with at least two end to end implementations.
  • Proven Enterprise/Solution/Delivery Architecture Experience in defining a modular architecture that can respond to current and future business requirements, business systems, and business processes evolving in the I & D areas.
  • Proven experience in pre-sales, leading large scale data & AI solutions (build and run) end to end, resulting into wins.
  • Experienced in at least one of industry standard architecture frameworks like TOGAF/IAF/NIST Big Data/Zachman/DODAF/FEAF/IndEA.
  • Proficiency in GenAI and Agentic AI, experience in GTM.
  • Experience building solutions that enable Large Language Models (LLMs) to securely interact with external tools, APIs, and enterprise systems (ERP, HCM, ServiceNow) utilizing the Model Context Protocol (MCP).
  • Strong understanding & experience of popular modern age MPPs such as Databricks, Cloud data warehouses like Snowflake, Redshift.
  • Knowledge of Enterprise Security, Data Management and Governance.
  • Ability to articulate pros & cons of “TO-BE” design/architecture decisions across a wide spectrum of factors.
  • Excellent knowledge of standard and big data/cloud native DWHs specific design patterns and paradigms.
  • Ability to engage in senior-level technology discussions.
  • The ideal candidate is pro-active, shows an ability to see the big picture and can prioritize the right work items in order to optimize the overall team output.
  • Should have worked in agile environments.
  • Excellent leadership skills, with the ability to generate stakeholder buy-in and lead through influence at a senior management level.
  • Strong verbal and written communication skills.
  • Ability to work in collaborative, cross functional, and multi-cultural teams.

Nice To Haves

  • Good to have exposure to DevOps/DataOps/MLOps/AIOps.
  • Architecture Certifications will be added advantage.
  • Good to have good history of thought leadership in the industry (social presence/persona, speeches, book critic/books, papers, conference presentations, academic lectures/faculty, etc.).

Responsibilities

  • Set technology direction, vision, and strategy to enable new I & D technology adoption.
  • Lead efforts to define cloud/data/AI future state architectures and roadmaps including architecture standards, guidelines, and industry best practices.
  • Demonstrate a leadership role in ensuring that new and existing systems are aligned to architectural guidelines.
  • Collaborate with architects in BUs to ensure comprehensive and cohesive working solutions are developed across disciplines with Economic and technical value proposition.
  • Work closely with development team to size, scale and tune existing and new architecture.
  • Benchmark systems, analyze system bottlenecks and propose solutions to eliminate them.
  • Clearly articulate pros and cons of various technologies and platforms.
  • Document use cases, solutions and recommendations.
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