Data Architect and Strategy - AI Integration & Deployment (Remote with travel)

We're looking for a Data Architect who is equal parts hands‑on builder and trusted strategic advisor. You'll be embedded in a high‑velocity GenAI application delivery engagement, owning the data architecture layer from design through to production – while also serving as the connective tissue between our delivery team and the client's data and engineering stakeholders.

What You’ll Do

• Architect the Data Foundation: Design and own the end‑to‑end data architecture underpinning GenAI application deployments – spanning ingestion, transformation, serving layers, and integration with existing enterprise data environments, including Databricks and legacy platforms.
• Get Hands‑On in the Stack: Work directly with application and ML teams to implement and validate data pipelines, schema designs, and data access patterns that power production‑grade AI applications built in Python/FastAPI.
• Bridge Two Worlds: Act as a high‑EQ consultant who can translate complex data architecture decisions into clear strategic narratives for client leadership – and then roll up your sleeves to implement them alongside the team.
• Set the Data Standards: Define and enforce data governance, quality, and lineage practices within the delivery environment. Ensure that what gets built is not just functional, but defensible, scalable, and ready for enterprise scrutiny.
• Enable the Client: Partner with client‑side data and engineering teams to build understanding and ownership of the new architecture. Leave behind capability, not dependency.

What You’ll Bring

• Senior Data Architecture Experience: 10+ years across data engineering, architecture, or a closely related discipline. You've designed systems that actually went to production – not just the whiteboard version.
• Modern Data Platform Fluency: Deep familiarity with lakehouse architectures, with hands‑on Snowflake experience strongly preferred. You understand how data flows from raw ingestion to AI‑ready serving layers.
• GenAI Context: Experience working in or adjacent to AI/ML application development. You understand how LLMs and AI applications consume data, and what that demands of the underlying architecture.
• Consulting & Stakeholder Acumen: Experience in a consulting or client‑facing delivery environment. You can build trust quickly, navigate organizational complexity, and communicate architecture decisions to both technical and non‑technical audiences.
• Builder Mentality: You're not just an advisor – you write code, build pipelines, and validate your own designs. Python fluency and comfort in cloud‑native data environments are expected.
• AI‑Ready Mindset: You embrace AI tooling as a force multiplier and are excited to operate at the intersection of modern data infrastructure and applied GenAI delivery.

Benefits

• Competitive salary with performance‑based bonus
• PTO, holidays, and sabbatical program
• Health, dental, vision, and life insurance
• Retirement plan with company match from day one
• Learning and professional development support
• Small‑firm culture with direct access to leadership