AWS Data Engineer
Job Description
Own AWS data engineering delivery end to end in a hybrid role in Rosemont, IL.
Responsibilities
- Own enterprise-scale data pipelines and cloud data warehouse solutions from design through deployment
- Build AWS-based pipelines using modern orchestration to support real analytics workloads across the company
- Architect and optimize an Amazon Redshift data warehouse powering 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 expand data access across the organization
- Bring medallion architecture and modern data standards to life
- Collaborate closely with IT and cross-functional teams in a lean environment where ideas move quickly
- Participate across build phases: 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- Identify broken or outdated components and implement improvements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 set team priorities based on technical knowledge
- Help shape the data engineering practice as the company scales rapidly
Requirements
- Recent, hands-on experience building and supporting solutions on AWS, 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 scheduling and managing data pipelines (e.g., Airflow or Step Functions)
- 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 showing depth in data engineering roles
- Strong analytical skills plus excellent written and verbal communication
- Comfort operating independently with minimal supervision while collaborating across teams
- Open to supporting legacy systems alongside newer technologies
Technologies
- AWS, IAM, S3, API Gateway, Glue, Lake Formation, Redshift
- RDS, DynamoDB
- Airflow, Step Functions
- Python, PySpark
Benefits
- 401(k)
- 401(k) matching
- Dental insurance
- Health insurance
- Life insurance
- Paid time off
- Parental leave
- Vision insurance
Nice to Have
- Exposure to AI or machine learning tooling in a data engineering context (for example, feeding pipelines into ML models, using 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.