Impetus - AWS Data Architect

Role & responsibilities : We are looking for a highly versatile and experienced Technical Architect who can design, build, and scale end-to-end technology solutions across multiple domains including Data Platforms, Application Development, Cloud, Machine Learning, and Generative AI.The ideal candidate is a multi-domain architect with strong fundamentals and the ability to architect across technologies, drive modernization initiatives, and guide teams in delivering scalable, secure, and high-performance systems.Key Responsibilities : 1. Enterprise Architecture & Solution Design : - Design end-to-end architectures spanning applications, data platforms, AI/ML systems, and cloud ecosystems.- Define architecture principles, standards, and best practices.- Create HLD/LLD design artifacts.- Ensure solutions are scalable, resilient, secure, and cost-efficient.2. Multi-Domain Technology Architecture : - Architect solutions across : 1. Application Development (monoliths, microservices, APIs)2. Data Platforms (Data Lakes, Lakehouse, Data Warehouses)3. Cloud-native systems (AWS / Azure / GCP)4. AI/ML & Generative AI solutions- Enable seamless integration across systems and domains.3. Application Architecture & Development : - Design modern application architectures (microservices, event-driven, API-first).- Define integration patterns (REST, GraphQL, messaging, streaming).- Ensure best practices in performance, scalability, and reliability.4. Data & Analytics Architecture : - Architect data ecosystems including ingestion, processing, storage, and consumption.- Support batch, streaming, and real-time processing.- Define data modeling, governance, lineage, and quality frameworks.5. AI/ML & Generative AI Enablement : - Design and integrate ML and GenAI solutions into enterprise platforms.- Define architectures for : 1. Model lifecycle (training, deployment, monitoring)2. LLM integration and AI pipelines- Ensure responsible, scalable AI implementations.6. Cloud & Platform Engineering : - Architect and implement solutions on AWS / Azure / GCP.- Leverage cloud-native services for applications, data, and AI workloads.- Drive platform engineering, scalability, and cost optimization (FinOps).7. Modernization & Transformation : - Lead application and data modernization initiatives : 1. Legacy - Cloud-native2. Monolith - Microservices3. Traditional DW - Modern Data Platforms- Define and execute migration strategies (rehost, replatform, refactor, rebuild).8. DevOps, Automation & Observability : - Implement CI/CD pipelines across application, data, and ML workflows.- Promote Infrastructure as Code (IaC) and automation.- Define monitoring, logging, and observability frameworks.9. Security, Governance & Compliance : - Implement end-to-end security architecture.- Define identity, access control, and data protection mechanisms.- Ensure compliance with enterprise and regulatory standards.10. Leadership & Collaboration : - Provide technical leadership and mentorship.- Collaborate with stakeholders, product teams, and engineering teams.- Contribute to solutioning, pre-sales, and innovation initiatives.- Drive adoption of modern engineering and architectural best practices.Preferred candidate profile : Required Skills & Experience : Core Technical Expertise : - Strong experience across : 1. Application Development2. Data Engineering & Platforms3. Cloud Architecture- Deep understanding of distributed systems and system design.Application Development : - Proficiency in Java, Python, or similar languages.- Experience with : 1. Microservices architecture2. API design and integration3. Event-driven systemsData & Analytics : - Experience with : 1. Data Lakes, Data Warehouses, Lakehouse architectures2. ETL/ELT pipelines and data modeling- Familiarity with big data processing frameworks.Cloud (Mandatory Any One) : - AWS / Azure / GCP with experience in : 1. Application services2. Data platforms3. AI/ML servicesAI/ML & GenAI (Preferred) : - Exposure to : 1. Machine Learning lifecycle and MLOps2. Generative AI / LLM-based solutions- Understanding of AI integration patterns.DevOps & Platform Engineering : - Experience with : 1. CI/CD pipelines2. Infrastructure as Code (Terraform or similar)3. Containerization (Docker, Kubernetes)Preferred Qualifications : - Experience in modernization and transformation programs.- Exposure to multi-cloud or hybrid architectures.- Certifications in cloud, architecture, or data engineering.- Experience in cost optimization and FinOps.Soft Skills : - Strong architectural thinking and problem-solving.- Excellent communication and stakeholder management.- Ability to translate business requirements into scalable solutions.- Leadership mindset with focus on mentoring and innovation. (ref:hirist.tech)