Platform Architect

Role & responsibilities

• Define and evolve the AI & data architecture vision, balancing innovation, scalability, and cost optimization
• Evaluate emerging technologies, tools and frameworks to enable modernization and automation
• Maintain architectural guardrails to ensure scalable, secure and cost effective delivery
• Evaluate emerging trends in AI, data platforms and cloud ecosystems to proactively shape the GTCs future state
• Collaborate with product managers and engineering teams to translate requirements into technical designs
• Guide engineering teams through design, build, and release phases ensuring reusability and performance
• Translate complex business requirements into modular, reusable architectural components across cloud-native environment • Develop architecture principles and coding standards for robust models and data pipeline deployments
• Manage AtScale cluster configurations and scaling policies
• Act as SME for high-impact technical escalations and complex design decisions
• Mentor and coach developers and engineers on architecture best practices
• Ensure strong documentation and maintain reusable design artefacts
• Provide technical leadership and support to cross-functional project teams
• Collaborate with data science teams to support ML/AI workload requirements
• Coordinate with DevOps teams on infrastructure automation and deployment practices
• Lead architectural review sessions and technical decision-making processes
• Drive knowledge sharing sessions and establish architectural communities of practice within the GTC

Preferred candidate profile

• 10-15 years of total experience in enterprise data architecture and platform engineering, with 3-4 years of leadership experience is preferred
• Extensive experience in designing and implementing large-scale data and machine learning architectures across cloud and hybrid environments
• Proven expertise in architecting scalable, reliable, and secure data solutions, with a strong focus on evaluating and adopting emerging technologies
• Hands-on experience in building and maintaining integrated data platform architectures, including components such as Snowflake, AtScale, and dbt
• Deep knowledge of Snowflake performance optimization, including usage monitoring, cost control strategies, and efficient resource scheduling
• Proficiency in designing data/AI systems using cloud-native platforms (Azure, GCP, AWS)
• Deep expertise in data engineering, data lake/lakehouse architectures, MLOps frameworks, and distributed computing
• Hands-on knowledge of data modelling, data pipelines, real-time streaming, and batch processing
• Ability to implement data quality frameworks, lineage tracking, and monitoring systems
• Familiarity with BI tool integrations (e.g., Tableau, Power BI) and AtScale connection protocols
• Experience with version control, coding standards, and collaboration workflows for data development teams
• Capability to establish disaster recovery and backup procedures for data platforms
• Ability to define architecture standards, conduct reviews, and develop governance models
• Experience mentoring and training technical teams (engineers, analysts)
• Exposure to ML/AI workload support and collaboration with data science teams
• Familiarity with infrastructure automation and working with DevOps teams
• Knowledge of cost allocation and chargeback models for multi-team environments
• Understanding of API integrations and platform data exchange protocols
• Ability to design and implement automated scaling and SLA monitoring/reporting
• Understanding of data governance, privacy regulations, and compliance frameworks in the Indian enterprise landscape