Senior Principal Data Architect or Enterprise Data/AI Architect

Position: Senior Principal Data Architect / Enterprise Data & AI Architect
Location: Irving, TX
Employment Type: Full-Time
Compensation: Competitive (Open)
Note: Local candidates preferred. Must be able to work onsite from our Irving, TX office.

Role Overview

We are seeking a highly experienced Senior Principal Data Architect / Enterprise Data & AI Architect to lead the design and execution of enterprise-scale data platforms and AI-driven solutions. This role will define the organization’s data strategy, architecture, and AI enablement roadmap, driving transformation across cloud, analytics, and next-generation AI capabilities.

Key Responsibilities

1. Strategy & Architecture

• Define and drive enterprise data strategy aligned with business, analytics, and AI objectives
• Design scalable lakehouse and modern data platform architectures supporting batch and real-time data processing
• Establish architectural standards, patterns, and best practices across the organization

2. AI & Advanced Analytics Enablement

• Build model-ready data foundations to support AI/ML and Generative AI use cases
• Design and implement agentic AI workflows using frameworks such as LangChain
• Architect RAG (Retrieval-Augmented Generation) pipelines and enterprise knowledge systems
• Enable data pipelines optimized for model training, inference, and LLM integration

3. Platform Engineering & Cloud Architecture

• Lead end-to-end data platform modernization and cloud migration initiatives
• Architect and optimize solutions across leading platforms:
o Snowflake: Multi-layer architecture (raw, curated, consumption), RBAC, data sharing, Cortex AI
o Databricks: Lakehouse architecture, Delta Lake, ML lifecycle, model serving
o Google BigQuery & Amazon Redshift: Serverless analytics and native integrations
• Optimize pipelines for performance, scalability, and cost efficiency across cloud ecosystems (AWS, Azure, Google Cloud Platform)

4. Data Governance & Security

• Establish enterprise-wide frameworks for data quality, observability, metadata management, and lineage
• Define and enforce data governance policies and standards
• Implement secure architectures including encryption, access controls, and compliance (e.g., HIPAA, SOC 2)

5. Leadership & Stakeholder Engagement

• Serve as a trusted advisor and technical authority to executive and senior stakeholders
• Lead and mentor data engineering, analytics, and AI teams
• Drive cross-functional collaboration across business, technology, and operations

Required Qualifications

Experience:

o 8–10 years in data engineering / data architecture
o 3–5 years in cloud data platforms and modern data ecosystems

Technical Expertise:

o Strong proficiency in SQL, Python, and Spark
o Deep experience in data modeling (Relational, Star Schema, Snowflake Schema, Data Vault)
o Hands-on experience with batch and streaming architectures

Cloud Platforms:

o Expertise in at least two: AWS, Azure, OCI, Google Cloud Platform
o Multi-cloud exposure is highly preferred

Preferred Qualifications

Certifications such as:

o SnowPro Core (Snowflake)
o Cloud Data Engineer certifications (AWS, Azure, Google Cloud Platform)

Proven, hands-on experience in at least two of the following platforms:

o Snowflake
o Databricks
o Google BigQuery
o Amazon Redshift

• Experience with Generative AI, LLMs, and enterprise AI architecture
• Exposure to FinOps, cost optimization, and large-scale data environments

Please send your resume in word format, following details to or call me @ for more information:
 
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