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Information Architect

India, Pune · Job Posted May 27, 2026
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Job Description

We are seeking an Information Architect who will translate business requirements into robust data and solution designs that enable effective development and analytics. This role focuses on data modelling and data warehouse design, working closely with business and technical stakeholders, and providing design guidance to delivery teams throughout the development lifecycle.

Job Responsibility

  • Translate business requirements into end-to-end solution and data designs
  • Design and maintain enterprise and dimensional data models aligned to analytics and BI needs
  • Define data transformations, aggregations, and integration logic for data warehouse solutions
  • Review solution designs produced by colleagues and provide constructive guidance
  • Support developers during build and implementation by clarifying design decisions
  • Collaborate with stakeholders across business and technology teams to ensure alignment
  • Contribute to continuous improvement of data architecture and delivery practices.

Requirements

  • Strong technical expertise in data warehousing and data modelling
  • Experienced in dimensional modelling concepts and practical implementation
  • Comfortable working with ETL design and development using industry-standard tools
  • Proficient in SQL, including complex transformations and data analysis (Teradata and WhereScape exposure is advantageous)
  • Skilled in interpreting data and applying data manipulation and analysis techniques
  • A clear and confident communicator who can engage diverse stakeholders
  • Organised, detail-focused, and able to deliver under pressure to tight deadlines
  • A collaborative problem-solver with an innovative mindset.

Nice to have

Teradata and WhereScape exposure is advantageous

What we offer

  • Exposure to complex, enterprise-scale data and analytics environments
  • Opportunities to collaborate with global stakeholders across business and technology
  • A role that enables influence over data design standards and best practices
  • Continuous learning through hands-on delivery and solution ownership
  • A supportive environment that values accountability, collaboration, and quality outcomes.

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