Own end-to-end AWS data engineering for enterprise-scale pipelines and cloud data warehouse solutions in a hybrid role based in Rosemont, IL.

Own enterprise-scale data pipelines and cloud data warehouse solutions from design through deployment
Build cloud-based pipelines using modern orchestration to support real analytics workloads across the company
Architect and optimize a Redshift data warehouse for business intelligence and reporting at scale
Drive ETL and data lake architecture decisions
Design and build APIs and API gateway integrations to connect systems and enable data access across the organization
Implement medallion architecture and modern data standards
Collaborate closely with IT and cross-functional teams in a lean environment where ideas move quickly
Participate across the build lifecycle: requirements, design, coding, testing, and deployment
Troubleshoot and support production platforms the business relies on daily
Identify broken or outdated components and implement improvements
Mentor less experienced engineers and help shape team priorities
Contribute to the growth of the data engineering practice as the company scales rapidly

Recent, hands-on experience building and supporting AWS solutions, including IAM, S3, API Gateway, Glue or similar integration services, Lake Formation, Redshift, and relational/NoSQL databases (RDS, DynamoDB)
Strong working knowledge of a modern workflow orchestration tool for pipeline scheduling and management (Airflow, Step Functions, or similar)
Proficiency in Python and PySpark for scalable data engineering
Experience developing and integrating APIs, including API gateway configuration
Solid understanding of relational database concepts and data modeling best practices
Familiarity with medallion-style or similarly layered data architecture standards
Stable, progressive career history demonstrating depth in data engineering roles
Strong analytical skills plus excellent written and verbal communication
Comfort working independently with minimal supervision while collaborating across teams
Openness to supporting legacy systems alongside newer technologies

Exposure to AI or machine learning tooling in a data engineering context (for example, pipelines feeding ML models, working with AWS AI services like SageMaker, or supporting AI-driven analytics use cases)

Location: Rosemont, IL (hybrid, 3 days onsite)

Compensation: USD 135,000 - 150,000 per year

AWS Data Engineer

Job Description