Senior AI Data Architect — Enterprise Data Platform

3Pillar; United States; On-site; USD 180,000 - 250,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Disability Insurance

Life Insurance

AD&D Insurance

Unlimited PTO

Paid parental leave

401K

Flexible Work Policy

Paid Holidays

Job summary

3Pillar is seeking an AI Data Architect to design, govern, and evolve the enterprise data platform powering all AI initiatives across the organization. You will own data contracts, architecture, and the end-to-end data stack to support RAG-based applications, dashboards, and autonomous agents.

This role requires deep experience with data lakehouse concepts, data mesh patterns, and event-driven architectures, plus hands-on work with vector stores and LLM-related tooling.

Qualifications

• 15+ years of hands-on data engineering and architecture experience.

Responsibilities

• Architect and own the enterprise AI data platform—the unified, governed layer used by AI systems across the organization.
• Design multi-domain data models (lakehouse, data mesh, event-driven) with clean lineage and versioned schemas.
• Define tools and technologies to develop automated data pipelines and write ETL processes in Python/Java/Scala.
• Own the full data stack: real-time streaming, batch processing, cloud storage and compute, and data quality/metadata management.
• Drive modernization of legacy pipelines to cloud-native, AI-ready architectures with cost, latency, and velocity improvements.

Skills

Python

SQL

Data Modeling

Data Governance

Data Architecture

ETL

Real-time Streaming

Security

Access Governance

Vector Stores

RAG

LLMOps

Tools

Databricks

Snowflake

AWS

Kubernetes

Terraform

GitHub Actions

LangChain

LlamaIndex

LLM APIs

Pinecone

FAISS

ChromaDB

OpenSearch

Neo4j

Kafka

Job description

3Pillar is seeking an AI Data Architect to design, govern, and evolve the enterprise data platform powering all AI initiatives across the organization. You will own data contracts, architecture, and the end-to-end data stack to support RAG-based applications, dashboards, and autonomous agents.

This role requires deep experience with data lakehouse concepts, data mesh patterns, and event-driven architectures, plus hands-on work with vector stores and LLM-related tooling.