Senior Manager, Data Architecture & Analytics

Role Purpose

The Senior Manager for Data Architecture & Analytics leads client projects involving data architecture, data modeling, data integration, engineering, platform solutions, statistical methods, and analytics. This position supports organizations in transitioning from fragmented data systems to cohesive and reliable architectures that enable trustworthy information, interoperability, secure reuse, and effective decision-making. The role bridges business priorities and governance demands with actionable technical designs and implementation roadmaps.

This manager oversees architects, engineers, analysts, and platform specialists, ensuring quality control of technical outputs and facilitating collaboration among business, data, security, and technology stakeholders. While recommending standards and solution options, final architecture decisions and deployment authority rest with authorized client teams. The position ensures technical work is thoroughly documented, testable, and transferable to client personnel, with clearly stated assumptions, dependencies, risks, and transition plans.

Key Responsibilities

• Lead the architecture, data modeling, integration, engineering, platforms, and analytics streams within client engagements.
• Evaluate existing data environments, including information flows, platforms, interfaces, data repositories, analytical tools, and technical limitations.
• Formulate architectural principles, current and target state views, transitional states, and detailed implementation roadmaps.
• Oversee conceptual, logical, and physical data modeling while ensuring ties to business glossaries and metadata.
• Define integration and interoperability standards such as APIs, data exchanges, pipelines, event-based systems, and managed data sharing.
• Assess platform and tool alternatives based on functional, non-functional, security, operational, and cost considerations.
• Design analytics architectures, including indicators, dashboards, and data products, aligned with business objectives and trusted data.
• Incorporate requirements relating to security, privacy, classification, data quality, lineage, retention, and system resilience into designs.
• Facilitate architecture review sessions and prepare options, trade-off analyses, and recommendations for client approval.
• Lead technical teams, enforce design quality gates, and resolve dependencies or inconsistencies across workstreams.
• Conduct reviews of technical specifications, models, interface designs, test documentation, and transition plans prior to submission to clients.
• Develop client capabilities through detailed walkthroughs, explanation of design rationales, documentation, and structured handover processes.

Minimum Requirements

Education

• Bachelor's degree in computer science, data engineering, information systems, or a related discipline.
• Master's degree is preferred.
• Equivalent combinations of relevant education and applicable consulting or implementation experience may also be considered.

Professional Experience

• Typically over 10 years’ experience in architecture, data engineering, or analytics, including at least 4 years in technical leadership roles.
• Proven leadership in data architecture, engineering, integration, or analytics programs within complex organizations.
• Ability to translate business and governance needs into technical solutions and transition roadmaps.
• Experience managing multidisciplinary teams including architects, engineers, analysts, platform specialists, and external technology vendors.
• Effective presentation of technical options and trade-offs to senior non-technical stakeholders.

Technical and Domain Expertise

• Knowledge of enterprise and data architecture methodologies, principles, and governance frameworks.
• Proficiency in conceptual, logical, and physical data modeling.
• Familiarity with integration approaches, including API design, data exchange mechanisms, pipelines, and interoperability strategies.
• Understanding of cloud-based, on-premises, and hybrid data platform architectures.
• Experience with analytics, reporting, indicator metrics, and dashboard architecture.
• Expertise in metadata management, data lineage, data quality measures, and master data design.
• Awareness of security, privacy, access controls, data retention policies, resilience planning, and operational requirements.
• Skills in technology evaluation, transition planning, and managing technical debt.

Core Competencies

• Enterprise and data architecture leadership.
• Advanced data modeling techniques.
• Management of analytics platform solutions.
• Integration and interoperability pattern design.
• Technical governance and quality assurance.
• Strong leadership and team management.
• Systems thinking and design governance.
• Informed technical judgment.
• Guiding technical discovery and architecture workshops.
• Communicating complex architectural concepts to business executives.
• Developing clear architectural documentation, roadmaps, and decision records.
• Handling multidisciplinary teams and managing design dependencies.
• Critically evaluating vendor proposals and validating technical evidence.
• Balancing strategic objectives with practical implementation constraints.
• Facilitating architectural decisions without formal authority.

Preferred Certifications

• TOGAF Enterprise Architecture Practitioner Certification
• Certified Data Management Professional (CDMP) Practitioner or Master level
• Cloud data-related certifications