Senior Data & AI Platform Engineer – Real-Time Enterprise

Jimmy Jazz; Chicago (IL); Hybrid; USD 130,000 - 170,000; Full time

Benefits offered by this job

Health insurance

401(k)

Life insurance

Disability insurance

Job summary

Sabert Corporation seeks a Data & AI Platform Engineer to design and optimize scalable data platforms and AI-driven solutions. The role supports enterprise‑wide decision making by integrating data across manufacturing, supply chain, finance and more.

The engineer will build pipelines, implement governance, and deploy AI models for forecasting, maintenance, and process optimization in a hybrid work setup.

Qualifications

• Proven experience designing, building, and optimizing scalable data platforms.
• Experience with data governance, quality frameworks, and MDM practices.
• Hands-on with real‑time data ingestion from manufacturing/OT environments.
• Experience deploying ML models to production and maintaining pipelines.

Responsibilities

• Design, develop, and maintain scalable data pipelines from SAP S/4HANA, MES, SCADA, CRM and more.
• Build and manage enterprise data environments including lakehouse architectures and ETL/ELT pipelines.
• Ensure data quality, governance, and master data management across systems.
• Develop, validate, and deploy analytics and ML models for forecasting and optimization.
• Collaborate with IT/OT and business to translate challenges into scalable AI solutions.

Skills

Data engineering

Data modeling

Database design

Lakehouse architecture

ETL/ELT

Python

SQL

Cloud platforms

Power BI

ML/AI concepts

Education

Bachelor’s or Master’s degree in Data Science/CS/Engineering

Tools

Microsoft Fabric

Azure

Databricks

Snowflake

SAP ecosystem

Power BI

Job description

Sabert Corporation seeks a Data & AI Platform Engineer to design and optimize scalable data platforms and AI-driven solutions. The role supports enterprise‑wide decision making by integrating data across manufacturing, supply chain, finance and more.

The engineer will build pipelines, implement governance, and deploy AI models for forecasting, maintenance, and process optimization in a hybrid work setup.