Principal Data Architect

Role: Principal Data Architect


Location: Flexible / Hybrid (NY/NJ)


Full Time job role

Role Overview


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.

Key Responsibilities


1. 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.

2. 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.

3. 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.

Required Skills & Expertise

• 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

Preferred Qualifications

• Experience in BFSI or regulated industries
• Exposure to large-scale AI transformation initiatives
• Certifications in cloud or data platforms (AWS/Azure/GCP/Snowflake/Databricks)