Data Engineer (AWS)

Location: Chicago, Illinois, United States

Base pay range: $94,145.00–$122,550.00 annually, plus potential bonus and/or long-term incentive compensation.

Company

hirify.global' Digital Technology team builds and maintains large-scale technology, data analytics, and digital solutions for the airline.

What you will do

• Architect, implement, and maintain robust data infrastructure supporting end-to-end data pipelines.
• Design and operate high-performance, cloud-native infrastructure, containerized and serverless platforms, and AWS-based automation tools.
• Develop resilient batch and real-time data pipelines using Spark, Python, Databricks, and Flink.
• Monitor, troubleshoot, and optimize distributed, highly available, horizontally scalable data infrastructure.
• Evaluate emerging cloud-native, microservices, and AI technologies to improve scalability, resilience, and developer productivity.
• Collaborate with business users, product owners, and cross-functional teams to translate requirements into practical data solutions.

Requirements

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
• At least 2 years of experience in data engineering or related roles.
• Proficiency in Python, SQL, and data processing frameworks including Spark and PySpark.
• Familiarity with AWS services such as Kinesis, Redshift, Glue, Athena, and S3.
• Ability to collaborate with business users and product owners to design optimized data pipelines.
• Must be legally authorized to work in the United States for any employer without sponsorship.
• Successful completion of the interview is required, and reliable, punctual attendance is an essential job function.

Nice to have

• Bachelor's degree in a field relevant to Machine Learning.
• At least 3 years of experience in data engineering or related roles.
• Advanced knowledge of machine learning algorithms and techniques.
• Experience deploying machine learning pipelines into production.
• Strong understanding of machine learning workflows and MLOps tools and practices for managing ML workflows at scale.

Culture & Benefits

• Medical, dental, vision, life, accident, and disability coverage.
• Parental leave, employee assistance program, commuter benefits, paid holidays, and paid time off.
• 401(k) and flight privileges.
• Equal opportunity employment and reasonable accommodations for applicants and employees with disabilities.

Hiring process

• Successful completion of an interview is required to meet the job qualifications.