Data Engineer: Cloud Pipelines for AI & Analytics

Network Distribution; Schaumburg, Northern (IL, KY); Hybrid; USD 100,000 - 130,000; Full time

Benefits offered by this job

Competitive compensation

Generous PTO

Summer/Flex Hours

Wellness Program

401k matching

Profit Sharing

Fun work environment

Job summary

Network Distribution is seeking a Data Engineer to design, build, and maintain scalable data pipelines for enterprise data and AI platforms. You will ingest, transform, and validate data from operational systems into reliable datasets that support reporting, analytics, and ML initiatives.

The role requires strong SQL and Python skills, experience with cloud data platforms (Snowflake/AWS), and a solid understanding of data modeling, governance, and performance optimization.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Data Science, or related field.
• 5+ years of data engineering or analytics engineering experience.
• Experience with data warehousing, data governance, and enterprise data platforms.
• Strong SQL, Python, and data manipulation skills.

Responsibilities

• Design, develop, and maintain data pipelines ingesting data from operational systems into data warehouse, data lake, and AI/ML environments.
• Develop data transformation and loading processes using SQL, Python, and modern data engineering tools.
• Integrate data from ERP, SaaS, APIs, cloud storage, and other enterprise systems.
• Develop and support ingestion processes using cloud services, APIs, file-based integrations, and data integration platforms.
• Perform data validation and quality checks to ensure accuracy and reliability.

Skills

SQL

Python

Data pipelines

Cloud platforms

Snowflake

AWS

ETL/ELT

Data modeling

Data governance

Education

Bachelor's degree in CS or related

Tools

Snowflake

AWS

dbt

Terraform

CI/CD

Git

Job description

Network Distribution is seeking a Data Engineer to design, build, and maintain scalable data pipelines for enterprise data and AI platforms. You will ingest, transform, and validate data from operational systems into reliable datasets that support reporting, analytics, and ML initiatives.

The role requires strong SQL and Python skills, experience with cloud data platforms (Snowflake/AWS), and a solid understanding of data modeling, governance, and performance optimization.