Enterprise Digital Twin Architect

Tata Consultancy Services Limited; Hyderabad; On-site; INR 5,000,000 - 7,500,000; Full time

Benefits offered by this job

Healthcare benefits

Job summary

Tata Consultancy Services Limited seeks a seasoned Enterprise Digital Twin Architect to lead design, governance, and evolution of Digital Twin capabilities across telecom and network engineering domains. You will drive maturity assessments, data modelling, AI enablement, and multi-domain data integration to support intelligent planning and automation.

Responsibilities include defining roadmaps, data models, KPIs, and value realization; collaborating with architecture, cloud, data, security, and

Qualifications

• Define KPIs, success measures, and value realization frameworks for Digital Twin initiatives.
• Lead architecture reviews, governance forums, capability assessments, and stakeholder workshops.
• Collaborate with architecture, engineering, operations, cloud, data, security, and AI teams.
• Experience in Telecom Network and Enterprise Digital Twin architecture and implementations.
• Experience designing and integrating Digital Twin platforms and enterprise data ecosystems.
• Knowledge of AI/ML, Generative AI, Intelligent Agents, AIOps, automation, orchestration, and predictive analytics.

Responsibilities

• Define and govern Enterprise Digital Twin architecture, frameworks, roadmaps, and operating models.
• Assess current Digital Twin maturity and define target-state capabilities.
• Design Digital Twin data models covering assets, services, resources, topology, telemetry, and states.
• Support AI, intelligent automation, orchestration, predictive analytics, and decision-support use cases.
• Conduct capability and maturity assessments and develop improvement roadmaps.
• Collaborate with multiple teams to establish Digital Twin adoption strategies.
• Strong expertise in Telecom Network and Digital Twin governance models.

Skills

Digital Twin architecture

AI/ML

Data Mesh

Data Fabric

Cloud technologies

API architectures

Telecom network

Data governance

Tools

Graph models

Semantic models

Data integration frameworks

Job description

Job Description:

Role Summary

Lead the design, assessment, governance, and evolution of Network Digital Twin capabilities across telecom and network engineering domains

Drive Digital Twin maturity assessments, data modelling, AI enablement, and integration of multi-domain data sources to support intelligent planning, decision support, operational visibility, and automation initiatives.

Key Responsibilities

• Define and govern Enterprise Digital Twin architecture, frameworks, roadmaps, and operating models.
• Assess current Digital Twin maturity and define target-state capabilities aligned with industry-recognized practices and capability models.
• Design Digital Twin data models covering assets, services, resources, dependencies, topology, telemetry, and operational states.
• Support AI, intelligent automation, orchestration, predictive analytics, and decision-support use cases enabled through Digital Twin capabilities.
• Conduct capability and maturity assessments and develop improvement roadmaps.
• Collaborate with architecture, engineering, operations, cloud, data, security, and AI teams to establish Digital Twin adoption strategies.
• Define KPIs, success measures, and value realization frameworks for Digital Twin initiatives.
• Lead architecture reviews, governance forums, capability assessments, and stakeholder workshops.
• Recommend technology platforms, graph models, semantic models, integration approaches, and Digital Twin operating principles.
• Ensure Digital Twin capabilities support secure, scalable, explainable, and reliable AI-enabled operations.
• Strong expertise in Telecom Network and implementation.
• Strong expertise in Enterprise Digital Twin architecture, design, and implementation.
• Experience conducting Digital Twin, automation, or operational capability maturity assessments.
• Expertise in Digital Twin governance models, operating frameworks, and adoption strategies.
• Experience designing and integrating Digital Twin platforms and enterprise data ecosystems.
• Knowledge of AI/ML, Generative AI, Intelligent Agents, AIOps, automation, orchestration, and predictive analytics.
• Strong understanding of Data Mesh, Data Fabric, metadata management, lineage, and data quality frameworks.
• Familiarity with cloud technologies, API architectures, event-driven integration patterns, and enterprise data integration frameworks.
• Experience developing enterprise Digital Twin adoption strategies supporting automation and AI initiatives.