Principal Data Architect

SolutionIT, Inc.
Hackensack, United States of America
5 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Hackensack, United States of America

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Azure
Data Architecture
Data Governance
Data Infrastructure
Machine Learning
Cloud Services
TensorFlow
Search Technologies
Enterprise Data Management
Google Cloud Platform
Cloud Platform System
Data Ingestion
Snowflake
Generative AI
Data Lineage
Data Management
Machine Learning Operations
Virtual Agents
Databricks

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)

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