Senior Solution Architect

About the Role

This position is a leadership role focusing on maintaining the technical soundness of enterprise solutions rather than direct hands-on coding or development. The architect is responsible for guiding multidisciplinary engineering teams through design and implementation phases and ensuring overall solution integrity without personally engaging in application or platform development.

Key Responsibilities

• Own and oversee the entire solution architecture including application, data, integration, cloud, security, and analytics domains.
• Convert business and technical requirements into comprehensive and actionable technical designs.
• Establish and document architecture principles, standards, design patterns, interface specifications, and major technical decisions.
• Provide leadership and technical guidance to diverse engineering and delivery teams, coordinating efforts across specialists and engineers as needed.
• Review proposed designs and development approaches to verify consistency with approved architectural frameworks.
• Implement an end-to-end quality management system covering all solution lifecycle aspects such as architecture, data, applications, integration, infrastructure, security, testing, deployment, and operations.
• Set quality benchmarks, controls, and acceptance criteria along with review processes and automated testing to ensure solution robustness, consistency, and maintainability.
• Continuously monitor solution quality during delivery phases, identify defects and systemic risks, conduct root cause analysis, and enforce corrective measures to promote ongoing improvement.
• Lead the resolution of complex technical challenges and manage cross-domain technical dependencies.
• Guarantee that security, privacy, data governance, performance, scalability, availability, and maintainability criteria are met.
• Drive adoption of DevOps best practices including automation, testing, monitoring, and engineering quality standards within delivery teams.
• Analyze and manage technical risks, technical debt, and readiness for solution releases.
• Collaborate closely with Project Managers on estimation, planning, sequencing of tasks, risk management, progress tracking, and ensuring readiness for delivery.
• Communicate complex architectural issues clearly to both technical and non-technical stakeholders, providing concise technical reports.

Required Qualifications and Experience

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, Computer Engineering, or a related field.
• Minimum 12 years in technology roles, with at least 5 years specifically in Solution Architecture, Technical Architecture, or comparable leadership positions, including recent experience leading architectural initiatives.
• Demonstrated success delivering sophisticated enterprise solutions integrating data platforms and applications, while leading multidisciplinary technical teams throughout the full delivery lifecycle.
• Proven authorship of essential architectural artifacts such as solution and interface designs, integration blueprints, non-functional requirements, security architectures, and documented architectural decisions.

Technical Expertise Areas

• End-to-End Solution Architecture covering source systems, data ingestion, processing, governance, semantic layers, analytics, APIs, and web applications.
• Data Platform Architecture including ETL/ELT processes, data integration, transformation, curation, modeling, quality, metadata management, cataloguing, lineage, governance, MDM/RDM, and semantic layers.
• Application & Integration Architecture focused on modern web architectures, APIs, API gateways, microservices, containerization, Kubernetes, and distributed systems patterns.
• Cloud and Platform Architecture involving cloud and hybrid environments, scalability, resiliency, networking, compute, storage, platform observability, and integrations.
• Security & Privacy Architecture featuring IAM, RBAC/ABAC, API security, encryption, masking, tokenization, data privacy controls, row/column-level security, and secure software development practices.
• Analytics and AI/ML technologies encompassing descriptive, diagnostic, predictive, prescriptive analytics, semantic modeling, and machine learning fundamentals.
• DevOps and Quality Engineering practices using Git, continuous integration/continuous delivery (CI/CD), release management, deployment automation, and automated quality assurance including unit, integration, regression, performance, static and dynamic application security testing (SAST and DAST).
• Agile Technical Delivery frameworks such as Scrum and Kanban, including backlog refinement, technical task decomposition, dependency and debt management, and release planning.