At CI&T, we are expanding our data and AI capabilities to deliver transformative solutions for our global clients. We are seeking a Senior Data Architect who will serve as a trusted technical advisor, bridging business strategy and cutting-edge cloud architecture. This role is critical in enabling our clients to modernize their data infrastructure, unlock AI-driven insights, and build scalable, future-ready data platforms.

The Senior Data Architect will lead the design and implementation of cloud-native data architectures, with a strong emphasis on AWS-based solutions and AI/ML readiness. This position requires a blend of deep technical expertise, strategic thinking, and exceptional client relationship management. You will work at the intersection of legacy system transformation and modern data platform design, guiding cross-functional teams through complex architectural decisions while keeping business objectives at the forefront. This engagement is part of a broader AI-first hyper-personalization initiative, requiring an architect who treats AI and ML workloads as first-class use cases from day one.

Responsibilities:

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

Requirements:

• Solid experience in data architecture roles with a strong focus on cloud technologies, specifically AWS

• Advanced English proficiency (C1 or above) required for client communication, technical documentation, and cross-functional collaboration
• Demonstrated experience designing data platforms that support AI and ML workloads as first-class use cases, including feature engineering, feature stores, and model serving infrastructure
• Proven expertise in navigating legacy data systems and implementing migration strategies to modern cloud platforms
• Experience with agentic AI technologies and enthusiasm for implementing AI-driven solutions in data architecture contexts
• Strong analytical and problem-solving skills to address complex, ambiguous data architecture challenges
• Excellent verbal and written communication skills, with the ability to articulate technical concepts to diverse audiences including executives, engineers, and business stakeholders
• AI-first mindset with demonstrated use of AI tools in daily technical work
• Experience with AWS Medallion Architecture (Bronze/Silver/Gold layers) and data lake design patterns

• Background in Data Mesh principles and federated data governance models

Nice to Have:

• Hands-on experience with MLOps platforms and infrastructure, including model training pipelines and deployment automation

• Familiarity with distributed data processing frameworks and technologies for large-scale data transformation
• Experience working in CPG, FMCG, Retail, or similar consumer-focused industries

• AWS certifications (Solutions Architect, Data Analytics, Machine Learning)