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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  • Identify broken or outdated components and implement improvements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.

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