Head - Enterprise Integration & Middleware

Job Role : Head - Digitization

Division : Support Section : IT/ITES

Role Overview :

To build and continuously improve digital ecosystem so that applications, data and digital tools operate as one integrated platform rather than as separate systems. The role will own the enterprise integration, data and digital - enablement layer across the organisation and will work closely with the Head - IT, business functions, application owners and implementation partners.

This position will work closely with Operations, IT, Finance, Supply Chain, Quality, and Leadership teams to build a data - driven and automated operations ecosystem.

Areas of Responsibilities Key Activities :Essential Functions :Key Responsibilities :1. Enterprise Integration & Middleware :

• Own the architecture and implementation of the enterprise integration layer.

• Ensure ERP, CRM, PLM, WMS, MES / shopfloor systems, customer portals and custom applications exchange information through a structured middleware and API architecture.

• Define integration standards, interface ownership, monitoring and failure - handling practices.

• Reduce uncontrolled point - to - point integrations and prevent new application silos.

• Coordinate integration requirements across internal teams, application owners and technology partners.

2. Master Data Management & Data Governance:

Implement and operate an enterprise MDM framework that creates trusted common master data.

• Define the system of record, business owner, approval workflow and distribution rules for key masters such as customers, vendors, products/materials, locations, assets and other shared enterprise data.

• Drive data quality, de - duplication and consistent use of master data across systems.

• Establish practical governance for ownership, changes, exceptions and data stewardship.

3. Enterprise Data Platform / Data Lake:

Design and progressively implement the central enterprise data platform.

• Bring governed data from ERP, CRM, PLM, WMS, MES and other applications into a common Data Lake / Lakehouse architecture.

• Establish reliable data pipelines, data models, lineage and quality controls.

• Make enterprise data usable for reporting, analytics, automation and AI while maintaining traceability back to source systems.

4. Business Intelligence & Enterprise Reporting:

Create a common reporting architecture with the objective of establishing one version of the truth for management information.

• Standardise KPI definitions and common business data definitions.

• Enable dashboards, management reporting and drill - down analytics from governed enterprise data.

• Progressively reduce contradictory reports, spreadsheet - based reporting and independent reporting logic embedded across departments.

5. Enterprise Digital Platforms:

Own and improve common digital platforms used across multiple business functions.

• Document Management System (DMS): document storage, versioning, access, workflow and lifecycle.

• Knowledge Management System (KMS): capture, search and reuse of organisational knowledge.

• Low - Code / No - Code platforms: rapid digitisation of smaller workflows and applications within defined architecture and governance standards.

• Enterprise AI agents / copilots: controlled deployment of AI for knowledge retrieval, document analysis, engineering assistance, workflow support and repetitive business tasks.

• RPA and other automation technologies where they are the appropriate solution.

6. Process Digitisation & Automation:

Partner with business functions to identify and eliminate manual, repetitive and disconnected processes.

• Translate business requirements into practical technology solutions.

• Choose the simplest appropriate solution: improve the existing enterprise application first, then workflow / low - code, RPA, AI or custom development where justified.

• Drive digitisation of processes currently dependent on paper, email, spreadsheets or manual transfer of information between systems.

• Measure business outcomes such as cycle - time reduction, productivity improvement, error reduction and adoption.

7. Digital Architecture & Standards:

Under the overall technology architecture and governance of the CIO, establish standards for the digital layer.

• Define standards for integrations, APIs, data models, MDM, workflow platforms, low - code applications and AI agents.

• Ensure new solutions fit the enterprise architecture and do not create another generation of disconnected tools.

• Work with cybersecurity and infrastructure teams to ensure solutions comply with enterprise security, access - control and technology standards.

8. Program, Vendor & Delivery Management:

• Convert business needs into clear BRDs / functional requirements and implementation plans.

• Support technology evaluation, vendor / SI selection, commercials and scope definition together with the CIO and relevant stakeholders.

• Manage implementation partners against agreed scope, timelines, cost, quality and business outcomes.

• Move initiatives from pilot to stable production and ensure ownership, support and adoption are established.

9. Adoption & Continuous Improvement:

• Track usage and adoption of digital platforms after implementation.

• Identify usability, process and data issues and drive continuous improvement.

• Build strong working relationships with business process owners and create appropriate functional ownership for digital solutions.

Candidate Profile:

• 12 - 18 years of relevant experience in enterprise applications, digital transformation, systems integration, data platforms or enterprise architecture.

• Strong preference for experience in a manufacturing, engineering or asset - intensive organisation.

• Demonstrated ability to translate business processes and requirements into scalable technology solutions.

• Experience working with implementation partners / system integrators and managing multi - functional technology programs.

• Ability to operate at both architecture and delivery level - technically strong enough to challenge vendors and design decisions, without needing to be the hands - on specialist in every platform.

Preferred Technical Exposure:

• ERP and surrounding enterprise systems such as CRM, PLM, WMS, MES and portals.

• Middleware, APIs and enterprise integration patterns.

• Master Data Management and data governance.

• Data Lake / Lakehouse / Data Warehouse platforms and enterprise data pipelines.

• BI and analytics platforms.

• DMS, KMS, workflow and Low - Code / No - Code platforms.

• AI / GenAI, enterprise agents / copilots and RPA.

Person Specification:Education, Language, Specifications & Qualifications:

• Bachelor's degree in Engineering, Computer Science, Information Technology or a related discipline. Relevant postgraduate qualifications or certifications in enterprise architecture, data, cloud or digital transformation are desirable.

• Process Automation Experience in Manufacturing Industries.

• Tenure Consistency.

• Flexible Mindset.

• Required 10 - 15 years of relevant experience in Project Deliveries & SAP Environment. Software Integration knowledge.

• Excellent written and spoken English. Should be from Mumbai.