Chief Data Architect

Aanseacore; Chennai District; On-site; INR 350,000 - 730,000; Full time

Job summary

Aanseacore is seeking an experienced Chief Data Architect to lead enterprise data architecture strategy, standards, and governance across the organization. You will drive MDM, metadata management, data quality, data lineage, and lifecycle programs to enable BI, analytics, AI, and digital transformation.

Candidates should have deep expertise in data platforms, data integration, canonical models, and interoperability, with hands-on architectural leadership and strong stakeholder engagement.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field; Master's degree preferred.
• 1520+ years of experience in Enterprise Data Architecture, Data Engineering, Data Governance, Information Management, and Enterprise Integration.
• Strong expertise in Enterprise Data Architecture, Data Governance, Master Data Management (MDM), Metadata Management, Data Modeling, Data Quality, Data Lineage, and Data Lifecycle Management.
• Hands-on experience designing enterprise data platforms for Business Intelligence, Analytics, Reporting, AI, and Machine Learning.
• Experience with enterprise platforms such as Oracle and other large-scale business applications.
• Strong knowledge of data integration, canonical data models, interoperability standards, and enterprise information architecture.
• Experience implementing DAMA-aligned data governance and lifecycle management practices.
• TOGAF certification preferred; DAMA-DMBOK and other Data Architecture or Cloud certifications are an advantage.
• Excellent leadership, stakeholder management, communication, and enterprise architecture governance skills.

Responsibilities

• Define and execute the enterprise data architecture strategy aligned with business and digital transformation goals.
• Establish and govern enterprise-wide data architecture standards, policies, and best practices.
• Design and implement Data Governance frameworks, stewardship models, and data ownership processes.
• Lead Master Data Management (MDM), Metadata Management, Data Quality, Data Lineage, and Data Lifecycle initiatives.
• Develop enterprise data models, canonical models, and integration standards to ensure consistency across platforms.
• Architect scalable data platforms supporting Business Intelligence, Analytics, Reporting, AI, and Machine Learning.
• Define standards for data ingestion, transformation, storage, orchestration, cataloging, and access control.
• Review data models, integration designs, and solution architectures to ensure compliance with enterprise standards.
• Lead architecture reviews, technical workshops, and governance forums while providing hands-on guidance for complex architecture decisions.
• Collaborate with Enterprise Architects, CIO, CDO, Security, Business, and Digital Transformation teams to align data architecture with organizational objectives.
• Mentor technical teams, implementation partners and vendors while ensuring adherence to enterprise architecture standards.
• Drive continuous improvement of enterprise data architecture capabilities, governance processes, and data management practices.

Job description

Job Description

We are seeking an experienced Chief Data Architect to lead the enterprise data architecture strategy and establish a scalable, secure, and governed data ecosystem. This role is responsible for defining enterprise data standards, governance, master data management, integration, and data platform architecture to support business intelligence, analytics, AI, and digital transformation.

Skill / Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field; Master's degree preferred.
• 1520+ years of experience in Enterprise Data Architecture, Data Engineering, Data Governance, Information Management, and Enterprise Integration.
• Strong expertise in Enterprise Data Architecture, Data Governance, Master Data Management (MDM), Metadata Management, Data Modeling, Data Quality, Data Lineage, and Data Lifecycle Management.
• Hands-on experience designing enterprise data platforms for Business Intelligence, Analytics, Reporting, AI, and Machine Learning.
• Experience with enterprise platforms such as Oracle and other large-scale business applications.
• Strong knowledge of data integration, canonical data models, interoperability standards, and enterprise information architecture.
• Experience implementing DAMA-aligned data governance and lifecycle management practices.
• TOGAF certification preferred; DAMA-DMBOK and other Data Architecture or Cloud certifications are an advantage.
• Excellent leadership, stakeholder management, communication, and enterprise architecture governance skills.

Job Responsibilities

• Define and execute the enterprise data architecture strategy aligned with business and digital transformation goals.
• Establish and govern enterprise-wide data architecture standards, policies, and best practices.
• Design and implement Data Governance frameworks, stewardship models, and data ownership processes.
• Lead Master Data Management (MDM), Metadata Management, Data Quality, Data Lineage, and Data Lifecycle initiatives.
• Develop enterprise data models, canonical models, and integration standards to ensure consistency across platforms.
• Architect scalable data platforms supporting Business Intelligence, Analytics, Reporting, AI, and Machine Learning.
• Define standards for data ingestion, transformation, storage, orchestration, cataloging, and access control.
• Review data models, integration designs, and solution architectures to ensure compliance with enterprise standards.
• Lead architecture reviews, technical workshops, and governance forums while providing hands-on guidance for complex architecture decisions.
• Collaborate with Enterprise Architects, CIO, CDO, Security, Business, and Digital Transformation teams to align data architecture with organizational objectives.
• Mentor technical teams, implementation partners and vendors while ensuring adherence to enterprise architecture standards.
• Drive continuous improvement of enterprise data architecture capabilities, governance processes, and data management practices.