Hands-On Big Data Architect - Hybrid Chicago
Core
Design, build, and optimize large-scale data platforms and pipelines to enable scalable data processing, analytics, and AI-enabled engineering use cases for clients.
Role type
Manager, Data Engineering (Hands-on IC)
Builds
End-to-end data solutions, batch and streaming pipelines, data foundations for AI/ML, and modern cloud data platforms.
Domain
Cloud Data Engineering & AI Engineering
Deliverable
production ML models
Required skills
Cloud data platforms (AWS/Azure/GCP), Databricks, Python, Column-oriented databases (BigQuery/Redshift), NoSQL (DynamoDB/Cosmos DB), SQL (SQL Server/Oracle/MySQL), ETL/Streaming frameworks (Glue/Spark/Dataflow), Data modeling (Lakehouse/Data Mesh), MLOps, AI Engineering patterns (RAG, context engineering, agent architectures), Vector/Graph databases, Agentic orchestration.
Preferred skills
Developer certifications (AWS/Azure/GCP/Databricks/Snowflake), Retail/Financial services industry experience, Snowflake zero-copy architecture, Agentic harnesses (Pi/Hermes), LLM evaluation infrastructure.
Technologies
Databricks, Delta Lake, AWS, Azure, GCP, BigQuery, Redshift, DynamoDB, Cosmos DB, Spark, Glue, Dataflow, Vertex AI, Azure AI, Snowflake, Pi, Hermes Agent.
Responsibilities
Lead design and delivery of large-scale data systems and platform modernization; Build and optimize batch/streaming pipelines; Support AI/ML deployment with data foundations and retrieval patterns; Automate platform operations and observability; Mentor junior team members; Conduct technical feasibility assessments.
Seniority
Manager, hands-on IC