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 setting • 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

📌 Platform Architect (Chennai)
🏢 HD Supply
📍 Chennai