Senior Manager-Enterprise Data Architect

• Work Model: Hybrid / Mandatory Work from Office as per client requirement
• Candidate Expectations
• Total Experience: 15+ Years
• Relevant Experience: 12+ years in Data Architecture, Enterprise Data Architecture, Data Strategy, Data Platform Architecture, Data Transformation, or related areas
• Candidate Location: PAN India
• Skills Mandatory: Enterprise Data Architecture. Data Strategy , Data Transformation, Data Governance, Cloud Data Architecture Azure / AWS / GCP, Data Lake / Lakehouse / Data Warehouse, Master Data Management (MDM).
• Candidate Industry:
• Preferred: Banking / Financial Services / Insurance / Capital Markets Also considered: Large Enterprise / Technology / Consulting / GCC / GBS / Captive environments with complex enterprise data transformation experience
• Education and Certification

Qualification Mandatory

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.

Good to Have:

• Master's degree in Computer Science, Information Technology, Data Science, Business Analytics, or related field.
• MBA / equivalent qualification from a reputed institution.

Specific Remarks:

• Regular full-time education preferred. Relevant experience and strong enterprise architecture expertise may be considered in lieu of higher academic qualifications, subject to client policy.
• Certification Good to Have: TOGAF, DAMA / CDMP, Cloud Architecture certifications AWS / Azure / GCP, Databricks / Snowflake certifications, Data Governance / Data
• Management certifications, Relevant AI/ML certifications

Role Overview

• Seeking an experienced Enterprise Data Architect / Data Architect with 15+ years of experience to define and drive enterprise data strategies, target-state architectures, data platform modernization, governance
• frameworks, and scalable data ecosystems.
• The candidate will be responsible for developing enterprise data architecture blueprints, reference architectures, integration patterns, data models, governance frameworks, and transformation roadmaps that enable enterprise analytics, AI/ML, GenAI, regulatory reporting, and broader business transformation initiatives.

Key Responsibilities

• Define and drive the enterprise data architecture ision,
• principles, standards, frameworks, and technology roadmaps aligned with business and technology strategy.
• Develop current-state and target-state data architectures and identify gaps, dependencies, risks, and modernization opportunities.
• Design enterprise data architectures covering: Data platforms, Data products, Data integration, Data governance, Metadata management, Master Data Management Develop conceptual, logical, and high-level physical data models supporting enterprise analytics, reporting, AI/ML, and operational requirements.
• Define scalable architecture patterns for data ingestion, transformation, storage, processing, consumption, and data sharing.
• Establish reusable reference architectures, architecture standards, design patterns, and best practices across data initiatives.
• Define enterprise integration patterns across: Operational applications, Cloud platforms, SaaS applications, APIs, Event-driven architectures, Streaming platforms, Enterprise data platforms Lead architecture decisions involving modern data platforms,
• including: Data Lakes, Data Warehouses, Lakehouse architectures, Data Mesh, Data Products.
• Evaluate and recommend appropriate cloud and data technologies based on business requirements, scalability, security,
• performance, cost, and integration considerations.
• Define architecture requirements for metadata, data cataloguing, data lineage, data quality, privacy, security, retention, compliance, and auditability.
• Establish architecture frameworks supporting Master Data Management, reference data, canonical data models, and enterprise data domains.
• Assess existing enterprise data landscapes and recommend modernization, migration, consolidation, and transformation strategies.
• Develop high-level implementation roadmaps, transition architectures, platform selection criteria, sizing considerations, and architecture decision frameworks.
• Provide architecture guidance for enterprise analytics and business intelligence initiatives.
• Partner with Data Engineering, Data Science, Analytics, Information Security, Data Governance, Enterprise Architecture, and Business teams to ensure alignment of data solutions with enterprise standards.
• Ensure architecture decisions address security, privacy, regulatory, compliance, resilience, scalability, performance, and auditability requirements.
• Develop and present architecture proposals, recommendations, roadmaps, and decision papers to senior business and technology stakeholders.
• Drive architecture governance and provide technical oversight across strategic data transformation programs.
• Identify emerging data, cloud, AI, and analytics technologies and assess their applicability to enterprise requirements.
• Key Skills: Enterprise Data Architecture. Data Strategy, Data Transformation, Data Governance, Cloud Data Architecture Azure / AWS / GCP, Data Lake / Lakehouse / Data Warehouse, Master Data Management (MDM).