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Lead Data Architect

Type:Full-time
Location:Lewisville, TX
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Lead Data Architect, Data & AI Platform
Hybrid – Lewisville, TX
Perm Role

Our client is seeking a hands-on Lead Data Architect to own the technical architecture of its modern Data & AI platform.

This role will lead data ingestion frameworks, data contracts and standards, and domain models supporting analytics, reporting, and machine learning.

The platform uses a Snowflake-centric medallion architecture and an AI-assisted development model.

The Lead Data Architect will establish architectural standards, review engineering and AI-generated work, and solve complex technical challenges across the platform.

Responsibilities:

Data Platform Architecture

  • Own the architecture of the Snowflake medallion platform across Bronze, Silver, Gold, and Publish layers.
  • Define standards and patterns for ingestion, transformation, conformance, and data publication.
  • Guide tooling and technology decisions across Snowflake, transformation, orchestration, and storage.
  • Ensure architecture supports current reporting needs and future AI/ML initiatives.

Data Modeling & Domain Design

  • Lead domain and dimensional modeling for Gold and Publish layers, from source analysis through physical implementation.
  • Design models supporting BI, reporting, and ML use cases.
  • Establish modeling standards, naming conventions, and design guidelines.
  • Review and approve data models across the team.

Ingestion & Data Contracts

  • Design reusable ingestion frameworks for CDC, APIs, messaging, SaaS extracts, and file-based sources.
  • Develop scalable ingestion patterns across a 40+ application environment.
  • Define data contracts, source-to-target mappings, and validation standards.
  • Partner with application teams to establish reliable, contract-backed data feeds.

AI-Assisted Development

  • Establish architecture standards and reusable guidance for AI-assisted engineering workflows.
  • Review and validate work produced by engineers and AI tools.
  • Continuously improve standards and development patterns based on team and platform needs.

Platform Operations & Reliability

  • Design for observability, data quality, troubleshooting, and efficient recovery.
  • Establish standards for data quality, reconciliation, and monitoring.
  • Guide warehouse and compute design for performance and cost efficiency.
  • Support security and role-based access control in partnership with governance and security teams.

Technical Leadership

  • Serve as the technical lead for complex architecture, performance, modeling, and ingestion challenges.
  • Mentor engineers through design reviews and technical collaboration.
  • Partner with governance and BI teams on contracts, metadata, mappings, and semantic models.
  • Clearly communicate technical decisions and trade-offs to technical and business stakeholders.

Skills:

Data Platform & Tools

  • Deep hands-on experience with Snowflake, including architecture, performance tuning, security/RBAC, and cost management.
  • Experience with modern ELT/transformation frameworks; Coalesce preferred, dbt acceptable.
  • Experience with Azure, including Data Factory and ADLS; Airflow is a plus.
  • Proficiency with Git, pull requests, and protected-branch workflows.

Data Modeling & Integration

  • Strong dimensional and domain modeling experience, including designing models from raw source data through implementation.
  • Strong understanding of grain, keys, conformance, and slowly changing dimensions.
  • Experience designing ingestion for CDC, APIs, messaging, and batch files.
  • Experience with contract-driven or schema-first integration.

AI-Assisted Engineering

  • Experience reviewing, directing, and correcting AI-generated engineering work.
  • Ability to translate architectural standards into clear, reusable guidance for both engineers and AI workflows.

Leadership & Operations

  • Experience with data quality, monitoring, incident diagnosis, and performance/cost optimization.
  • Strong ownership and problem-solving skills with the ability to work through ambiguity.
  • Ability to establish standards while keeping projects moving.

Education & Experience:

  • Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field; master's preferred.
  • 8+ years of experience in data engineering and architecture, including 3+ years owning platform- or domain-level architecture decisions.
  • Proven experience designing and operating cloud data platforms in production.
  • Experience establishing and enforcing technical standards, contracts, naming conventions, and review processes.

Preferred Experience:

  • Automotive, insurance claims, or repair/estimate data experience.
  • Data contract specifications and contract-driven development.
  • Migration of legacy SQL Server, SSIS, or SSAS environments to modern cloud platforms.
  • Experience with agentic or AI-assisted engineering tools in an enterprise environment.