Project Role Data Architect Project Role Description Define the data requirements and structure for the application Model and design the application data structure storage and integration Must have skills Data Architecture Principles Valuable to have skills NA Minimum 7 5 year s of experience is required Educational Qualification 15 years full time education Summary We are looking for a highly experienced and technically proficient Generative AI Data Architect AWS with deep expertise in data architecture principles data modeling techniques and methodologies and enterprise-scale AI ML systems The ideal candidate should have 10-13 years of experience in designing and managing complex data platforms with a strong foundation as a Data Modeler This role will lead architectural decisions for Gen AI and LLM-based systems ensuring the data layer is optimized for performance scalability and AI integration Roles Responsibilities 1 Architect scalable and modular data platforms on AWS to support Gen AI LLMs and advanced analytics use cases 2 Lead and own data modeling efforts across conceptual logical and physical layers ensuring models align with AI ML application needs 3 Define implement and govern data architecture principles data flow patterns lineage and transformation logic 4 Integrate and manage LLMs vector databases and semantic search infrastructure e g RAG pipelines 5 Translate Gen AI requirements into data architecture designs leveraging cloud-native patterns and tools 6 Collaborate with data engineers ML scientists and application developers to ensure data infrastructure meets the performance scalability and security needs of Gen AI applications 7 Establish data governance quality and metadata management frameworks 8 Drive data lifecycle management lineage tracking and model optimization for both structured and unstructured data assets 9 Conduct design reviews build architecture documentation and advise on Gen AI tool selection and integration strategies 10 Lead the design and deployment of real-time and batch data pipelines that power Gen AI applications Professional Technical Skills 1 Data Modeling Expertise 2 Strong command of data modeling techniques including 3NF dimensional modeling star snowflake schemas data vault and ontology modeling 3 Experience using tools like Erwin ER Studio dbt or SQL Power Architect 4 Ability to model and optimize data for AI LLM-ready formats e g text embeddings vector representations 5 In-depth knowledge of data lake Lakehouse data warehouse and data mesh architectures 6 Experience designing end-to-end data platforms for AI ML workloads using AWS native tools 7 Gen AI LLMs Practical experience integrating LLMs e g OpenAI Cohere Hugging Face Bedrock into applications 8 Proficiency in vector databases e g FAISS Pinecone Weaviate and building RAG Retrieval-Augmented Generation architectures 9 Familiar with prompt engineering embedding models and LLM orchestration frameworks e g Lang Chain 10 Cloud Infrastructure Advanced experience with AWS services S3 Redshift Glue Lake Formation Athena Lambda SageMaker Bedrock 11 Proficient in Terraform or CloudFormation for infrastructure provisioning 12 Data Engineering Experience with ETL ELT pipelines streaming Kafka Kinesis batch processing Spark Glue 13 Strong hands-on skills in SQL Python PySpark and API integrations 14 Governance Security Deep understanding of data governance lineage data cataloging e g AWS Glue Catalog Amundsen and compliance GDPR HIPAA 15 Familiarity with role-based access IAM encryption KMS and secure data architectures 16 Architecture Frameworks Knowledge of TOGAF Zachman or enterprise architecture best practices Additional Information Experience 10 to 13 years of experience in data architecture data modeling and enterprise-scale AI ML projects Education Bachelor s or master s degree in computer science Data Engineering Information Systems or related fields 15 years full time education

📌 Data Architect (Telangana)
🏢 Accenture
📍 Telangana