Lead / Principal Data Architect

Lead / Principal Data Architect – AI/ML & Modern Data Warehouse

Naperville / Chicago, IL (On-Site) 🕒 Full-Time

Grey Parrot Systems (GPARROT) is hiring a Lead / Principal Data Architect with deep AI/ML experience and hands-on expertise in modern data warehouse architecture — MotherDuck, dlt, dbt, and cloud-native data platforms.

About Grey Parrot Systems

Grey Parrot Systems (GPARROT) is a women-owned, BEP-certified IT services firm headquartered in Naperville, IL. We partner with mid-market enterprises to deliver AI-first, governance-driven digital transformation. Our team of seasoned CIO/CTO practitioners works side-by-side with clients across retail, logistics, manufacturing, and healthcare — and we're growing.

About the Role

This is a principal-level architecture role for a Data Architect who has modernized enterprise data warehouses, built AI/ML-ready data platforms, and knows how to design for scale, governance, and observability from day one. You will lead data architecture decisions across client engagements — defining the blueprint for modern, cloud-native data platforms using MotherDuck/DuckDB, dlt, dbt, and AI-integrated pipelines. If you think in data models, move with architectural precision, and are passionate about modernizing legacy data environments into AI-ready platforms — this role is for you.

What You'll Do

• Define and own data architecture strategy across client engagements — from legacy assessment to modern cloud-native data warehouse design
• Lead the modernization of legacy data warehouses to MotherDuck/DuckDB-based architectures — designing for scale, performance, and AI-readiness
• Architect and oversee dlt-based ELT pipelines for ingesting data from diverse enterprise sources
• Design and govern dbt transformation layers — models, tests, documentation, and data contracts
• Build AI/ML-ready data platforms — feature engineering pipelines, vector stores, embedding layers, and RAG-ready data architectures
• Define and implement data governance frameworks — lineage, observability, data quality, and access controls
• Collaborate with data engineers, ML engineers, and business stakeholders to align data architecture with business goals
• Establish data architecture standards, best practices, and reusable patterns across GPARROT engagements
• Evaluate and recommend emerging data tools and platforms to continuously modernize the data stack
• Mentor and upskill data engineers on modern data architecture patterns and AI-integrated workflows

What You'll Do

• Define and own data architecture strategy across client engagements — from legacy assessment to modern Medallion-based cloud-native data warehouse design
• Architect and implement Medallion Architecture frameworks — Bronze (raw ingestion), Silver (cleansed and conformed), and Gold (business-ready and AI-ready) layers
• Lead the modernization of legacy data warehouses to MotherDuck/DuckDB-based Medallion architectures — designing for scale, performance, and AI-readiness
• Architect and oversee dlt-based ELT pipelines for ingesting raw data into the Bronze layer from diverse enterprise sources
• Design and govern dbt transformation layers across Silver and Gold — models, tests, documentation, and data contracts
• Build AI/ML-ready Gold layer datasets — feature engineering pipelines, vector stores, embedding layers, and RAG-ready data architectures
• Define and implement data governance frameworks across all Medallion layers — lineage, observability, data quality, and access controls
• Collaborate with data engineers, ML engineers, and business stakeholders to align Medallion architecture with business and AI goals
• Establish data architecture standards, Medallion best practices, and reusable patterns across GPARROT engagements
• Evaluate and recommend emerging data tools and platforms to continuously modernize the data stack
• Mentor and upskill data engineers on Medallion Architecture patterns and AI-integrated data workflows

Tech Stack

MotherDuck · DuckDB · dbt · dlt · Python · SQL · Airflow · Azure / AWS / GCP · Snowflake · BigQuery · Azure OpenAI · LLM APIs · Vector Databases · Feature Stores · Data Lineage Tools · Apache Kafka · CI/CD Pipelines

Nice to Have

• Experience with RAG pipeline architecture and vector database design (Pinecone, Weaviate, pgvector)
• Familiarity with MLOps platforms and ML feature store design
• Experience with real-time streaming data architectures — Kafka, Azure Event Hubs, or AWS Kinesis
• Knowledge of data mesh or data lakehouse architectural patterns
• Cloud certifications — Azure Data Engineer (DP-203), AWS Data Analytics, or GCP Professional Data Engineer
• Experience in retail, logistics, manufacturing, or healthcare data environments

Details

• Location: Naperville, IL — On-Site
• Experience: 8–12 years
• Type: Full-Time
• Start: Immediate

Grey Parrot Systems is an Equal Opportunity Employer. As a women-owned, BEP and WBENC-certified firm, diversity and inclusion are core to who we are. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, marital status, or any other legally protected characteristic. We strongly encourage applications from candidates of all backgrounds, identities, and experiences — including those from underrepresented groups in technology. Reasonable accommodations are available upon request.

Stay Connected

For more job openings, company updates, and AI industry insights, follow Grey Parrot Systems on LinkedIn.

👉 https://www.linkedin.com/company/gparrot/

We are always looking for talented, driven professionals to join our growing team. Whether this role is the right fit today or not, connect with us and be the first to hear about new opportunities as we expand across Chicago, Detroit, and the Midwest.

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