Lead Data Architect _ Exp: 12+ Years

Atyeti Inc; Gurugram District; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Atyeti Inc in Gurugram is looking for a Data Architect. The role involves designing and implementing scalable data architectures, leading comprehensive data modeling, and ensuring robust data quality frameworks.

Ideal candidates should possess strong knowledge of financial domain workflows and expertise in integrating AI/ML components. The position requires a deep understanding of cloud platforms and event-driven systems.

Qualifications

• Strong knowledge in designing scalable, end-to-end data architectures.
• Experience in comprehensive data modeling and quality frameworks.
• Familiarity with AI/ML components in data architectures.

Responsibilities

• Design and implement scalable, end-to-end data architectures.
• Lead comprehensive data modeling efforts across various layers.
• Create semantic data models and validate data integrity.
• Analyze domain-specific failure modes in data workflows.

Skills

Data architecture design

Data modeling (3NF, dimensional)

Semantic data models

Financial domain knowledge

AI/ML integration

Data quality frameworks

Distributed systems

Cloud platforms (AWS, Azure, GCP)

Performance optimization

Job description

• Design and implement scalable, end-to-end data architectures encompassing source system ingestion, integration pipelines, cloud-native data platforms, data mesh and downstream analytical and operational consumption layers, ensuring robustness, scalability, and security.
• Lead comprehensive data modeling efforts across conceptual, logical, and physical layers, applying best practices in normalized (3NF) and dimensional modeling to support complex, high-volume financial datasets and enable effective reporting and analytics.
• Create and maintain semantic data models using ontologies and validate data integrity via SHACL shapes to build enterprise knowledge graphs, establishing consistent terminology, enforcing data quality constraints, enhancing data interoperability.
• Possess strong knowledge of end-to-end workflows relevant to financial domains (e.g., trade lifecycle, processing, reporting, reconciliation), and design data architectures that optimize data movement, quality, and lineage throughout these workflows.
• Drive execution of technology strategies by translating business and technical requirements into actionable short-to-medium term technology roadmaps aligned with organizational goals.
• Integrate AI/ML or agent-enabled components into data architectures with a focus on reliability, explainability, operational controls, and graceful failure handling.
• Design and enforce data quality frameworks incorporating metadata management, lineage tracking, controls, and auditability to meet regulatory and operational compliance requirements.
• Analyze domain-specific failure modes—such as late or missing data, data mismatches, reconciliation discrepancies, and regulatory deadlines—and architect systems that proactively detect, surface, and remediate these issues.
• Serve as a trusted, domain-aware technical partner to engineering managers and delivery teams, providing guidance and hands-on support to ensure architectural integrity and delivery excellence.
• Possess strong experience designing and building distributed, data-intensive, event-driven systems within financial services or similarly regulated environments, emphasizing resilience and scalability.
• Produce detailed architectural designs and reference implementations; collaborate closely with engineering teams to translate designs into production-quality systems.
• Exercise sound judgment regarding system behaviour in production environments, including performance optimization, failure mode management, resilience, recovery strategies, and risk isolation.
• Demonstrate practical expertise with cloud platforms (AWS, Azure, GCP), leveraging managed services, multi-tenant architectures, and balancing cost-performance trade-offs effectively.
• Maintain hands‑on involvement in reviewing, writing, and improving production code; collaborate with senior engineers to solve complex technical challenges and ensure high-quality deliverables.