Client Advisory & Strategic Alignment
Drive architectural strategy discussions with client leadership to ensure data platform initiatives align with business objectives and deliver measurable value
Act as the senior technical voice in client engagements, translating complex architectural decisions into business outcomes for both technical and executive audiences
Manage client relationships from an architectural perspective, building trust through technical excellence and strategic insight
Technical Leadership & Team Enablement
Lead cross-functional teams of data engineers, data scientists, and analytics specialists in designing and deploying scalable, cloud-native data platforms
Support teams in planning and execution, providing architectural guidance and removing technical blockers throughout the delivery lifecycle
Mentor team members on cloud architecture best practices, data modeling principles, and emerging technologies
Cloud Architecture & Modernization
Design and implement robust AWS-based data lake architectures using Medallion (Bronze/Silver/Gold) patterns, managing trade-offs in storage strategies, partitioning schemes, and schema evolution
Lead the transition of legacy data structures and systems to modern cloud platforms, developing migration strategies that minimize risk and maximize business continuity
Architect solutions that balance performance, cost, scalability, and maintainability across complex data ecosystems
Business-to-Data Translation
Partner with Data & Analytics Managers and business stakeholders to translate business requirements into feasible, scalable architectural decisions
Define data models, integration patterns, and platform capabilities that directly support business use cases and analytics needs
Navigate complex, siloed data landscapes to design practical solutions that deliver value incrementally
AI/ML-Ready Platform Design
Design data platforms that natively support AI and ML workloads, including feature engineering pipelines, feature stores, model training data preparation, and inference serving infrastructure
Architect MLOps capabilities as a core platform component, not an afterthought, ensuring seamless integration of machine learning lifecycle management
Implement solutions leveraging agentic AI technologies to optimize data management, automate data quality workflows, and enhance analytics capabilities
Governance & Data Mesh Implementation
Advise on governance models (centralized vs. federated) appropriate to organizational structure and data maturity
Implement Data Mesh principles to enable domain-oriented ownership while maintaining platform-level standards and interoperability
Define data quality frameworks, metadata management strategies, and security/privacy controls that scale across distributed architectures
Innovation & AI-First Approach
Integrate AI tools and methodologies into daily architectural work, demonstrating innovative approaches to design, documentation, and problem-solving
Stay current with emerging data and AI technologies, evaluating their applicability to client challenges and incorporating them into platform strategies