Lead Data Architect

RedStream Technology; Lewisville (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

RedStream Technology seeks a hands-on Lead Data Architect to own the technical architecture of its modern Data & AI platform and shepherd data ingestion, domain modeling, and data contracts across the stack.

You will design and govern the Snowflake-based medallion architecture, set standards, review AI/engineered work, and enable scalable data feeds for analytics and ML use cases.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.
• 8+ years of data engineering/architecture experience with platform/domain ownership.
• Proven production experience designing cloud data platforms.
• Experience enforcing standards, contracts, naming conventions, and reviews.

Responsibilities

• Own Snowflake medallion platform architecture (Bronze-Silver-Gold-Publish).
• Define ingestion, transformation, conformance, and publication standards/patterns.
• Guide Snowflake, transformation, orchestration, and storage tech decisions.
• Support current reporting and future AI/ML initiatives.

Skills

Snowflake

Data architecture

ELT/ETL

dbt

Azure Data Factory

ADLS

Git workflows

AI/ML data

Education

Bachelor's degree in CS/IS/Engineering

Master's degree preferred

Tools

Snowflake

Coalesce

dbt

Azure Data Factory

Airflow

Git

Job description

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

• 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.
• 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.