Purpose

Conduct a comprehensive technical assessment of the existing data, analytics, reporting, and integration ecosystem to identify architecture weaknesses, performance bottlenecks, scalability concerns, data quality issues, governance gaps, and operational risks. Provide strategic recommendations and a target-state architecture to improve reliability, maintainability, scalability, and overall platform effectiveness.

Key Responsibilities

Architecture Review

• Review the existing data architecture, reporting architecture, and integration landscape.
• Assess current-state databases, data warehouses, semantic models, and reporting platforms.
• Evaluate the scalability, maintainability, reliability, and performance of the overall architecture.
• Identify architectural debt, design limitations, and areas of technical risk.
• Recommend architectural improvements aligned with business and technology objectives.

Data Platform Assessment

• Review data pipelines, ETL/ELT processes, transformation logic, and end-to-end data flows.
• Assess data lineage, data quality controls, reconciliation processes, and governance mechanisms.
• Identify inefficiencies, duplicated logic, and data consistency issues across systems.
• Analyze source-to-report data flows and transformation layers.
• Evaluate data management practices and recommend optimization opportunities.

Infrastructure & Performance Assessment

• Assess database performance, query optimization, refresh processes, and resource utilization.
• Review platform configurations, deployment environments, operational processes, and monitoring capabilities.
• Identify performance bottlenecks impacting reporting, refresh reliability, and platform stability.
• Evaluate disaster recovery, backup strategies, business continuity, and operational resilience.
• Recommend infrastructure enhancements to improve scalability and performance.

Integration & Connectivity Review

• Review system integrations, APIs, replication processes, and connectivity architecture.
• Assess the reliability and efficiency of data movement between source systems and analytical platforms.
• Identify latency issues, failure points, and integration risks.
• Recommend improvements to integration architecture, automation, and monitoring practices.
• Evaluate integration governance and operational support processes.

Business Intelligence & Reporting Assessment

• Review reporting architecture, semantic models, dashboards, and analytical solutions.
• Identify duplication, inefficiencies, performance issues, and scalability concerns.
• Assess adherence to BI best practices, standards, and governance frameworks.
• Evaluate reporting usability, data consumption layers, and information delivery mechanisms.
• Recommend enhancements to reporting design, performance, and user experience.

Key Deliverables

• Current-State Technical Architecture Assessment
• Data Pipeline and Integration Review Report
• Infrastructure and Performance Assessment Report
• Data Quality and Governance Gap Analysis
• Architecture Risk Register
• Technical Debt Assessment
• Future-State Architecture Blueprint
• Prioritized Remediation and Improvement Roadmap
• Executive Summary with Strategic Recommendations

Required Experience

• Minimum 8 years of experience in Enterprise Architecture, Solution Architecture, Data Architecture, Data Engineering, or related leadership roles.
• Strong expertise in:
  • Data Warehousing
  • ETL/ELT Architecture and Data Integration
  • Database Performance Optimization
  • Enterprise Integrations and API Architecture
  • Business Intelligence and Analytics Platforms
  • Data Governance, Data Quality, and Master Data Management
  • Cloud and On-Premises Data Platforms
• Proven experience conducting enterprise architecture reviews, technology assessments, and transformation initiatives.
• Strong analytical, problem-solving, and stakeholder management skills.
• Experience developing target-state architectures and technology modernization roadmaps.
• Excellent communication and presentation skills, with the ability to engage both technical and business stakeholders.

Preferred Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related field.
• Relevant industry certifications in Cloud Platforms, Enterprise Architecture, Data Management, or Analytics technologies are preferred.
• Experience working within large-scale enterprise environments and complex data ecosystems.