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Data Engineer
Job Title: Data Engineer Location: Hybrid, Chicago, IL <br> About the Role: Our company is seeking a Data Engineer with 5–7 years of experience in data engineering. This role is designed for individuals who excel at building robust, scalable data solutions in AWS cloud environments. As part of our team, you’ll engineer and optimize data pipelines critical to our analytics, reporting, and data-driven strategy, while collaborating cross-functionally in a hybrid Chicago-based setting. <br> Key Responsibilities: <br> Design, build, and maintain scalable data pipelines and architectures using AWS cloud services. Develop, manage, and optimize ETL/ELT workflows to acquire, clean, and transform data from diverse sources. Collaborate with business stakeholders, analysts, and data scientists to understand data requirements and deliver solutions. Ensure data quality, integrity, and security throughout all stages of the data lifecycle. Monitor pipeline performance and troubleshoot issues to maximize data reliability and efficiency. Apply data governance best practices and maintain technical documentation. <br> Must-Have Technologies: Languages: Python, SQL Cloud: AWS (S3, Redshift, Glue, Lambda, RDS, Data Pipeline) Big Data: Apache Spark, Hadoop, Kafka ETL Tools: Airflow, AWS Data Pipeline Databases: PostgreSQL, MySQL, Redshift, MongoDB Work Arrangement: <br> Hybrid schedule with regular in-office collaboration in Chicago, IL. Preferred Certifications (optional): <br> AWS Certified Data Analytics – Specialty AWS Certified Solutions Architect Certified Data detail oriented (CDP)
Requirements: 5–7 years of experience as a Data Engineer or equivalent role. Bachelor’s degree in Information Technology, Computer Science, or relevant experience in the field. Proficiency in Python and SQL. Hands-on expertise with AWS cloud tools such as S3, Redshift, Glue, Lambda, and RDS. Experience with big data frameworks (e.g., Apache Spark, Hadoop, Kafka). Familiarity with ETL orchestration tools (e.g., Airflow, AWS Data Pipeline). Solid understanding of data warehousing concepts and architecture. Experience with DevOps tools (e.g., Git, Docker, CI/CD) is a plus. Strong communication and documentation skills.
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  • Chicago, IL
  • remote
  • Temporary
  • 50.00 - 65.00 USD / Hourly
  • Job Title: Data Engineer Location: Hybrid, Chicago, IL <br> About the Role: Our company is seeking a Data Engineer with 5–7 years of experience in data engineering. This role is designed for individuals who excel at building robust, scalable data solutions in AWS cloud environments. As part of our team, you’ll engineer and optimize data pipelines critical to our analytics, reporting, and data-driven strategy, while collaborating cross-functionally in a hybrid Chicago-based setting. <br> Key Responsibilities: <br> Design, build, and maintain scalable data pipelines and architectures using AWS cloud services. Develop, manage, and optimize ETL/ELT workflows to acquire, clean, and transform data from diverse sources. Collaborate with business stakeholders, analysts, and data scientists to understand data requirements and deliver solutions. Ensure data quality, integrity, and security throughout all stages of the data lifecycle. Monitor pipeline performance and troubleshoot issues to maximize data reliability and efficiency. Apply data governance best practices and maintain technical documentation. <br> Must-Have Technologies: Languages: Python, SQL Cloud: AWS (S3, Redshift, Glue, Lambda, RDS, Data Pipeline) Big Data: Apache Spark, Hadoop, Kafka ETL Tools: Airflow, AWS Data Pipeline Databases: PostgreSQL, MySQL, Redshift, MongoDB Work Arrangement: <br> Hybrid schedule with regular in-office collaboration in Chicago, IL. Preferred Certifications (optional): <br> AWS Certified Data Analytics – Specialty AWS Certified Solutions Architect Certified Data detail oriented (CDP)
  • 2025-11-12T21:53:54Z

Data Engineer Job in Chicago | Robert Half