About the role

Role Overview

Data Engineer 3 responsible for designing, developing, and maintaining scalable cloud data solutions with a focus on data quality, pipeline reliability, and cloud-based data architecture.

Work model: Remote (U.S. time zone) or onsite/hybrid depending on the customer preference across Chicago, Dallas, Peoria, Champaign, or Westminster. Duration: Long-term (12 months with potential extension up to 2 years), with potential to lead to permanent employment.

Responsibilities

Design, develop, and maintain data pipelines with high data quality and reliability
Troubleshoot and resolve data issues using root-cause analysis and break/fix fixes
Build Python scripts and automation tools to detect and correct data issues
Create monitoring and alerting to proactively identify pipeline failures
Collaborate with cross-functional teams to improve data architecture, governance, and performance

Required Qualifications

Bachelor’s or Master’s in Computer Science, Engineering, or related field (or equivalent experience)
5–7 years experience in data engineering / data management / data operations
Strong AWS experience (e.g., S3, RDS, Lambda, DynamoDB, SNS, SQS)
Experience with Snowflake and cloud data platforms
Proficiency in SQL and Python
Experience with data pipelines, data quality, and data governance processes

Preferred Qualifications

Experience with AWS SageMaker and CloudWatch; strong advanced cloud architecture knowledge
Strong Snowflake and data warehousing knowledge
Experience supporting data operations / Tier 2 data support environments
Understanding of the end-to-end data lifecycle and big data technologies
Ability to thrive in a fast-paced, cross-functional environment

About Cullerton Group

Cullerton Group is a staffing and consulting organization that supports long-term engineering and design opportunities with client organizations. The role described will support a global leader in heavy machinery and manufacturing by building and maintaining scalable cloud data solutions.