Data Architect

Location

• PCS CHE, Chennai
• Years of Experience 7-10 Years

Job Summary

Responsibilities

• Architect the Data Foundation Layer to manage raw and standardized source data effectively.
• Engineer the Feature Store Layer to support reusable, governed model features, including lineage management and refresh frequency.
• Define and implement core Feature Store entities to ensure consistency and reusability.
• Design the Model Execution Layer architecture for seamless production scoring inputs and outputs.
• Establish a comprehensive Monitoring & Governance Layer to track KPIs, data drift, model performance, and explainability.
• Organize the data architecture around key business objects like Counterparties, Loans, Facilities, and Exposures.
• Design and deploy scalable batch and real-time feature ingestion pipelines using modern data engineering frameworks.
• Collaborate with cross-functional teams to define data quality standards, metadata frameworks, and MLOps practices.

Mandatory Skills

• Proven experience as a Data Architect with a focus on feature management ecosystems.
• Strong understanding of data architecture principles and best practices.
• Experience with data ingestion pipelines and modern data engineering frameworks.
• Expertise in managing data lineage, calculation logic, and governance.

Preferred Skills

• Familiarity with AI/ML concepts and practices.
• Experience in working with cloud-based data platforms.
• Knowledge of data quality and metadata management frameworks.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
• 7-10 years of relevant experience in data architecture and engineering.
• Strong analytical and problem-solving skills.

Responsibilities

• Proven experience as a Data Architect with a focus on feature management ecosystems.
• Strong understanding of data architecture principles and best practices.
• Experience with data ingestion pipelines and modern data engineering frameworks.
• Expertise in managing data lineage, calculation logic, and governance.