Lead Data Architect

• 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.