Enterprise Architect Data and Analytics

Job Description
Enterprise Architect Data & Analytics
Experience Required: 10 16 years overall IT experience; 5 7+ years in data/analytics architecture and enterprise reporting ecosystems

1. Background
TCS partners with our customers on enterprise data, analytics, and reporting modernization initiatives, including BI platform assessments and migrations from legacy reporting tools to modern tools.
The Enterprise Architect (Data & Analytics) provides architectural leadership across data platforms, analytics ecosystems, and enterprise reporting architectures, ensuring alignment with business goals, governance standards, and long-term data strategy.

2. Skills Required

• Strong experience in enterprise data and analytics architecture
• Expertise with BI and reporting platforms (Power BI, Tableau, enterprise reporting ecosystems)
• Experience defining semantic layer strategy, dataset governance, and analytics consumption patterns
• Understanding of modern data platforms (warehouse/lake/lakehouse) and data pipeline patterns
• Knowledge of enterprise integration patterns for data ingestion and data product enablement
• Experience with metadata management and data catalogs (concepts and patterns)
• Experience with data governance, data quality, lineage, and stewardship models
• Awareness of privacy, security, and regulatory considerations impacting enterprise data
• Ability to embed governance-by-design into data architecture recommendations
• Ability to translate business analytics needs into architecture designs and roadmaps
• Experience producing executive-ready architecture artifacts and recommendations

3. Responsibilities

• Define and maintain enterprise data architecture blueprints (sources, flows, transformations, quality, governance, and security)
• Assess current-state data, analytics, and reporting architectures; identify gaps, risks, and opportunities for modernization
• Define target-state analytics/BI architecture (semantic layer, dataset strategy, reporting ecosystem evolution) and migration pathways
• Establish and govern enterprise standards for data modeling, metadata, and platform patterns; drive consistency across domains
• Drive data governance controls (quality, lineage, access, compliance) and ensure architecture aligns with privacy/security expectations
• Define roadmap recommendations for data platforms and storage approaches balancing performance, cost, and compliance
• Partner with stakeholders to capture analytics requirements and translate them into architecture decisions and non-functional expectations
• Ensure BI modernization programs align to enterprise data standards and governance expectations
• Produce executive-ready architecture recommendations and assessment deliverables