Principal Data Architect
Job Location:
Job Location:
New York City, NY - USA
Monthly Salary:
Not Disclosed
Monthly Salary:
Posted on:
16 days ago
Posted on:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Role: Principal Data Architect
Location: Hybrid (NY/NJ)
Job Type: Full Time
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 hyperscalers (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
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- 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)
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- Implement AI governance controls to:
- Mitigate model hallucinations
- Ensure explainability and reliability
- Protect data privacy and regulatory compliance
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- 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)
