Data Architect and Strategy – AI Integration, Deployment

This is a fully remote position, open to applicants in Ohio.

📋 Description

• Design and oversee the comprehensive data architecture that supports GenAI application deployments, covering the entire process from ingestion and transformation to serving layers, and integration with existing enterprise data systems, such as Databricks and legacy platforms.

• Engage directly with application and ML teams to build and test data pipelines, schema designs, and data access patterns that facilitate production-grade AI applications developed in Python/FastAPI.

• Lead proactive data integration efforts by anticipating data requirements instead of reacting to them. Collaborate closely with integration architects, addressing technical gaps to ensure project momentum.

• Serve as a high-EQ consultant capable of translating intricate data architecture decisions into clear strategic narratives for client leadership, and actively participate in their implementation alongside the team.

• Establish and uphold data governance, quality, and lineage standards within the delivery environment. Ensure that the solutions developed are not only functional but also defensible, scalable, and suitable for enterprise evaluation.

• Collaborate with client-side data and engineering teams to foster understanding and ownership of the new architecture, ensuring a legacy of capability rather than dependency.

⛳️ Requirements

• Extensive experience in Senior Data Architecture: Over 10 years in data engineering, architecture, or a closely related field. You have successfully designed systems that have been implemented in production, not just theoretical models.

• Proficiency in Modern Data Platforms: In-depth knowledge of lakehouse architectures, with hands-on experience in Snowflake highly preferred. You comprehend how data progresses from raw ingestion to AI-ready serving layers.

• Familiarity with GenAI Context: Experience in or around AI/ML application development. You understand how LLMs and AI applications utilize data and the implications for the underlying architecture.

• Insight into Application Development: A robust understanding of the full application development lifecycle. You possess the expertise to recognize how data architecture integrates with the larger system.

• Consulting and Stakeholder Skills: Experience in a consulting or client-facing role. You can quickly establish trust, navigate organizational complexities, and effectively communicate architectural decisions to both technical and non-technical stakeholders.

• Builder Mentality: You are more than an advisor; you code, construct pipelines, and validate your designs. Proficiency in Python and comfort in cloud-native data environments are essential.

• AI-Ready Mindset: You view AI tools as a force multiplier and are enthusiastic about working at the intersection of modern data infrastructure and applied GenAI delivery.

🏝️ Benefits

• Competitive salary with performance-based bonuses

• Paid time off, holidays, and a sabbatical program

• Health, dental, vision, and life insurance coverage

• Retirement plan with company match from day one

• Support for learning and professional development

• A small-firm culture with direct access to leadership