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.