Architect – Data Engineering

• Strategy and Planning
  

• Define and evolve the 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 GTC’s future state.
  

• Delivery & Execution
  

• 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.
  
  

• Support & Enablement
  

• 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.
  
  

• People Leadership
  

• Provide technical leadership and support to cross-functional project teams.
  
• Collaborate with data science teams to support AI/ML 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.
  

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field.
  
• Certifications in cloud architecture (AWS, Azure, GCP), data modeling and AI/ML platforms preferred.
  

• 9–12 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 AI/ML 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.
  

Benefits

• Be part of a globally recognized organization committed to innovation, operational excellence, and sustainability.
  
• Opportunity to contribute to a rapidly growing Global Technology Center (GTC) in Chennai, supporting global engineering initiatives.
  
• Exposure to a diverse technology landscape and collaboration with cross-functional global teams.
  
• Competitive compensation and comprehensive employee benefits.
  
• Strong career growth pathways with continuous learning and development opportunities.