Principal Data Architect

Soni's client is seeking a Principal Data Architect to lead enterprise-wide data architecture strategy across relational, NoSQL, vector, and graph database ecosystems. This is the most senior individual contributor role within the data architecture function and will serve as the primary technical authority for modern data platform design, governance, and scalability.

This role partners closely with executive leadership, engineering, analytics, security, and product teams to define scalable data foundations that support analytics, AI/ML, and operational systems. Leadership is exercised through technical expertise, strategic influence, and mentorship rather than direct people management.

Responsibilities

Enterprise Data Architecture & Strategy

• Define and evolve enterprise data architecture across relational, NoSQL, vector, and graph database paradigms.
  
  
• Establish standards for data modeling, platform interoperability, and integration patterns.
  
  
• Translate business strategy into scalable data architecture decisions supporting analytics, AI/ML, and operational use cases.
  
  
• Recommend architectural and operational improvements that influence organizational decision-making.

Data Platform Leadership

• Own enterprise data modeling and schema standards for cloud data platforms.
  
  
• Review and approve major schema, warehouse, and data product design changes.
  
  
• Establish architecture review processes, standards, and governance checkpoints.
  
  
• Drive platform scalability, reliability, performance optimization, and cost efficiency.

AI/ML Data Foundations

• Design AI/ML-ready data architectures, including feature stores, embedding pipelines, and retrieval systems leveraging vector and graph technologies.
  
  
• Support LLM, analytics, and operational AI use cases through scalable data infrastructure.
  
  
• Evaluate emerging technologies and recommend innovative approaches to support growth and efficiency.

Technology Evaluation & Architecture Governance

• Lead technical evaluations, proof-of-concepts, and adoption strategies for new data technologies.
  
  
• Develop migration and modernization roadmaps for enterprise data platforms.
  
  
• Resolve complex cross-functional data architecture challenges through proactive design leadership.

Data Governance & Quality

• Define and enforce data governance, lineage, quality, security, and access standards.
  
  
• Partner with security, compliance, and analytics stakeholders to ensure enterprise-grade controls.
  
  
• Monitor data platform quality and recommend continuous improvement initiatives.

Technical Leadership & Mentorship

• Mentor engineers and architects across the organization.
  
  
• Serve as the lead reviewer for major data initiatives and architectural decisions.
  
  
• Present architecture strategy, roadmaps, and technical trade-off analyses to executive leadership.
  
  
• Build alignment across teams through influence and technical credibility.

Qualifications

Required

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
  
  
• 10+ years of experience in data architecture, data engineering, or database engineering with increasing technical leadership responsibilities.
  
  
• 3+ years of hands-on experience designing and operating enterprise-scale cloud data platforms.
  
  
• Deep expertise in data modeling, database design, and enterprise integration patterns.
  
  
• Strong understanding of modern data architecture patterns including ELT/ETL, CDC, streaming, and event-driven systems.
  
  
• Experience communicating complex technical concepts to executive and technical audiences.
  
  
• Demonstrated ability to navigate ambiguity and influence cross-functional technical decisions.

Preferred

• Experience with modern data stack technologies such as dbt, Airflow, and related tooling.
  
  
• Experience with at least one major cloud platform (AWS, Azure, or GCP).
  
  
• Familiarity with data governance, lineage, and security tooling.
  
  
• Experience supporting AI/ML or advanced analytics initiatives.
  
  
• Background in highly regulated, multi-site, or enterprise-scale environments.

Compensation: $140,000 to $150,000 annually
Compensation is based on a range of factors that include relevant experience, knowledge, skills, other job-related qualifications.