Principal Data Architect
Role details
Job location
Tech stack
Job description
The Principal Data Architect will lead the design and evolution of enterprise-scale data and AI platforms, enabling advanced analytics, Generative AI, and data-driven decision-making. This role requires deep expertise across cloud ecosystems, modern data architectures, and AI/ML frameworks, with a strong focus on governance, scalability, and security. Responsibilities: Data Platform Architecture
- Architect scalable, high-performance cloud data platforms across hyperscaler's (AWS, Azure, Google Cloud).
- Design and implement modern data stack solutions leveraging technologies such as Snowflake and Databricks.
- Define data ingestion, transformation, and serving architectures supporting real-time and batch workloads.
- Drive standardization of data architecture patterns across the organization.
AI & Machine Learning Architecture
-
Design and implement architectures for:
-
Generative AI solutions
-
Retrieval-Augmented Generation (RAG)
-
Vector databases and semantic search frameworks
-
Agentic AI frameworks and orchestration patterns
-
Define and operationalize MLOps and LLMOps pipelines for model lifecycle management.
-
Enable scalable deployment and monitoring of AI/ML models in production environments.
Data Governance, Security & Compliance
-
Establish enterprise-wide data governance frameworks covering:
-
Data quality and validation standards
-
Data lineage and traceability
-
Master Data Management (MDM)
-
Implement AI governance controls to:
-
Mitigate model hallucinations
-
Ensure explainability and reliability
-
Protect data privacy and regulatory compliance
-
Define access control, encryption, and security best practices for data and AI platforms
Requirements
- Strong experience in cloud platforms: AWS, Azure, or Google Cloud
- Deep expertise in modern data platforms: Snowflake, Databricks
- Hands-on experience in AI/ML architecture, including GenAI and RAG
- Knowledge of vector databases (e.g., Pinecone, FAISS, or equivalent)
- Experience with MLOps/LLMOps tools and frameworks
- Strong understanding of data governance, privacy, and compliance standards
- Proven ability to design and scale enterprise data platforms
Leadership & Stakeholder Management
- Provide architectural leadership across multiple programs and portfolios
- Collaborate with business, engineering, and AI teams to align architecture with business outcomes
- Mentor senior engineers and architects on best practices, * Experience in BFSI or regulated industries
- Exposure to large-scale AI transformation initiatives
- Certifications in cloud or data platforms (AWS/Azure/GCP/Snowflake/Databricks)