Senior Manager-Enterprise Data Architect

Golden Opportunities; Hyderabad, Chennai District; Hybride; INR 3 200 000 - 5 200 000; Plein temps

Résumé du poste

Golden Opportunities in India seeks an experienced Enterprise Data Architect with 15+ years of experience to define enterprise data strategies, target architectures, and data platform modernization.

You will develop architectures, data models, governance frameworks, and roadmaps for analytics, AI/ML, and regulatory reporting; collaborate with data engineering, security, and business teams while ensuring security, privacy, and compliance. The role is hybrid with client-driven office requirements.

Qualifications

• Bachelor’s degree in CS/IT/Engineering/Data Science or a related discipline.
• 15+ years total experience in data architecture or related domains.
• 12+ years in relevant architecture roles.
• Knowledge of data platforms, governance and cloud architectures.
• TOGAF, DAMA/CDMP or cloud certs are a plus.
• Excellent stakeholder communication and leadership.

Responsabilités

• Define and drive enterprise data architecture vision, 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 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.
• Lead architecture decisions involving modern data platforms, including: Data Lakes, Data Warehouses, Lakehouse architectures, Data Mesh, Data Products.
• Evaluate and recommend cloud and data technologies based on business requirements, scalability, security, performance, cost, and integration.
• Define architecture requirements for metadata, data cataloguing, data lineage, data quality, privacy, security, retention, compliance, and auditability.
• Establish architecture frameworks for Master Data Management, reference data, canonical data models, and enterprise data domains.
• Assess existing landscapes and recommend modernization, migration, consolidation, and transformation strategies.
• Develop high-level implementation roadmaps, transition architectures, platform selection criteria, sizing considerations, and decision frameworks.
• Provide architecture guidance for enterprise analytics and business intelligence.
• Partner with Data Engineering, Data Science, Analytics, Information Security, Data Governance, Enterprise Architecture, and Business teams to ensure alignment with standards.
• Ensure architecture decisions address security, privacy, regulatory, compliance, resilience, scalability, performance, and auditability requirements.
• Develop and present architecture proposals, roadmaps, and decision papers to senior 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.

Connaissances

Enterprise Data Architecture

Data Strategy

Data Transformation

Data Governance

Cloud Data Architecture

Data Lake

Data Warehouse

MDM

Architecture Frameworks

Formation

Bachelor's degree in CS/IT/Engineering/Data Science

Master's degree in CS/IT/Data Science/Business Analytics

MBA / equivalent qualification

Description du poste

• 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).