This position is no longer accepting applications
Closed on September 29, 2026.
This role is filled — get an email when new Data Processing roles open on DataJobs.io:
AWS Data Engineer
Amazon Web Services
AWS
Aws Api Gateway
Aws Glue
Business Intelligence
Cloud
Cloud Computing
Cloud Data Warehouse
Data Architecture
Data Engineer
Data Integration
Data Lake
Data Pipeline
Data Platform
Data Processing
Data Warehouse
Database
Databases
Dynamodb
ETL
View similar jobs
Get alerted when similar jobs are posted — set up a New Data Processing jobs on DataJobs.io alert.
See other roles at MMD Services, Inc.
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- Identify broken or outdated components and implement improvements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.