Role Summary:

We are seeking an experienced Program Manager with strong Enterprise Data Architecture expertise to lead governance, oversight, and successful delivery of the Enterprise Data Platform (EDP) program.

The role will serve as the single accountable owner for ensuring that external implementation partners deliver a scalable, secure, high-quality, and business-aligned data platform. The incumbent will govern architecture decisions, delivery milestones, data governance practices, security controls, integration standards, testing, and operational readiness.

Post go-live, the role will transition into owning platform operations, partner management, support governance, continuous improvement, business adoption, and implementation of future data and AI initiatives.

Key Responsibilities:

- Act as the overall EDP Program Manager responsible for delivery governance.

- Establish and manage program plans, milestones, risks, dependencies, and budgets.

- Conduct weekly, bi-weekly, and monthly governance reviews.

- Track partner performance against agreed SLAs and KPIs.

- Drive issue resolution and executive escalations when required.

- Present program updates to CIO, Steering Committee, and business leadership.

EDP Architecture Governance:

- Ensure adherence to enterprise data architecture standards and principles.

- Validate data models, schema design, and overall platform architecture.

- Review and approve solution architecture, data models, integration patterns, security architecture, and platform design decisions.

- Conduct Architecture Review Boards (ARB).

- Ensure long-term scalability and maintainability of the platform.

Partner Oversight & Solution Assurance:

- Govern implementation partners and ensure contractual deliverables are met.

- Review partner deliverables including data pipelines (batch & streaming), data ingestion frameworks, data models & semantic layers.

- Ensure solutions meet performance, scalability, and cost-optimization goals.

- Challenge and validate partner design decisions to avoid sub-optimal implementations and technical debt.

- Review partner resource plans, skill alignment, and knowledge continuity.

Data Governance & Compliance:

- Ensure implementation of data lineage, metadata management, cataloging, and data quality frameworks & scorecards.

- Govern data classification, PII handling, and regulatory compliance (incl. DPDP).

- Define and enforce data standards, naming conventions, and governance controls.

- Align data ownership and stewardship across business functions.

Integration Oversight (SAP + Enterprise Systems):

- Ensure seamless integration across SAP (ECC / S/4HANA), other systems (SFDC, Wondersoft, Vinculum, Shopify, etc.), and analytics platforms (Power BI, AI use cases).

- Validate data ingestion strategies and transformation logic (ETL/ELT).

Platform & Cloud Architecture Control:

- Validate cloud architecture (Azure / GCP / Databricks) for scalability, availability, cost optimization (storage, compute, egress), and data lifecycle management (archival, retention).

- Ensure proper implementation of RBAC / ABAC access controls, encryption, audit logging, and security layers.

Data Quality & Observability:

- Define KPIs and SLAs for data quality and pipeline performance.

- Ensure monitoring, alerting, and observability mechanisms are implemented.

- Track and enforce data quality improvements across domains.

Security, Compliance & Risk Management:

- Ensure compliance with information security, audit, and regulatory requirements.

- Govern disaster recovery, backup, and business continuity for the platform.

- Lead periodic security and access reviews.

Testing, UAT & Deployment Governance:

- Oversee data validation during UAT cycles and data reconciliation between source systems and EDP.

- Validate cutover strategy for historical data migration and incremental data loads.

- Ensure readiness for production and hypercare phases.

Documentation & Knowledge Governance:

- Ensure completeness and quality of architecture design documents, data dictionaries, and schemas.

- Establish documentation standards and governance processes.

- Drive structured knowledge transfer from partner to internal teams.

Post Go-Live BAU Ownership:

- Own day-to-day EDP platform governance and stability post go-live.

- Manage support partners / AMS teams against agreed SLAs and KPIs.

- Prioritize enhancement requests and continuous improvement initiatives.

- Maintain operational playbooks and knowledge repositories.

- Drive platform adoption across business functions.

Data & AI Enablement:

- Position the EDP as the trusted foundation for Analytics, AI, and GenAI use cases.

- Govern data readiness and availability for AI/ML and self-service BI.

- Partner with business teams and Data Champions to accelerate adoption.

Stakeholder & Leadership Engagement:

- Work with business, IT, and analytics teams to align EDP with business outcomes.

- Provide regular updates to leadership (CIO, Steering Committee).

- Facilitate decision-making on architecture, trade-offs, and investments.

Required Skills & Competencies:

Technical Expertise:

- Strong experience in Enterprise Data Architecture (Lakehouse / Data Warehouse), cloud platforms (Azure, Databricks preferred), and data modeling and large-scale data integration.

- Deep expertise in Data Governance, Data Quality, Metadata, Lineage, and security frameworks (RBAC / ABAC, encryption, audit).

- Exposure to SAP data models (ECC / S4) and enterprise integrations.

Programme & Leadership Skills:

- Proven programme management capability (planning, budgeting, risk, governance).

- Strong partner / vendor management capability.

- Ability to review, challenge, and approve architecture designs.

- Experience leading large-scale transformation programmes (EDP / ERP / AI).

- Strong communication and executive-level reporting skills.

Qualifications:

- Bachelor's / Master's degree in IT / Computer Science.

- 12+ years in Data Engineering / Architecture roles, with recent experience in a programme leadership capacity.

- Proven experience governing external implementation partners on enterprise-scale platforms.

Success Metrics (KPIs):

- EDP programme delivered on time and within approved budget.

- Data quality score meets or exceeds agreed target.

- Platform availability / uptime meets agreed SLA.

- Partner SLA and milestone adherence.

- Successful UAT sign-off and stable hypercare / BAU transition.

- User adoption across business functions and reduction in manual reporting effort.

- AI and analytics use cases successfully enabled on the EDP.