Data Platform Reliability Engineer

ittihad medical centre; Chicago (IL); On-site; USD 185,000 - 225,000; Full time

Job summary

IMC is seeking a data-focused engineer to support the Performance Team’s data platform. The role centers on reliability, correctness, and performance of data systems that feed performance analysis and decision-making.

The position is production-facing and collaborates with the Performance team to ensure data workflows are robust, observable, and efficient. Strong Python, PySpark, and Pandas skills are essential, with experience in production ETL environments.

Qualifications

• 3+ years in software or data engineering with production focus.
• Bachelor's Degree in Computer Science or related field preferred.
• Proficiency in Python with PySpark and Pandas.
• Experience supporting production ETL or data processing systems.

Responsibilities

• Own the operational health of the Performance Team’s data platform.
• Monitor and maintain ETLs and data pipelines for correctness, timeliness, and stability.
• Design and maintain data quality checks, reports, and alerting specific to performance data.
• Investigate and resolve data issues and pipeline failures, driving problems to root cause.
• Own and troubleshoot GitLab CI/CD pipeline issues related to performance data workflows.
• Monitor workloads and resource usage; identify and resolve imbalances and bottlenecks.
• Build and maintain operational tooling, automation, and runbooks.
• Continuously tune data pipelines and workloads to improve performance and resource efficiency.

Skills

Python

PySpark

Pandas

ETL pipelines

Analytical skills

Education

Bachelor's degree in Computer Science or related field

Tools

GitLab CI/CD

Git

Job description

IMC is seeking a data-focused engineer to support the Performance Team’s data platform. The role centers on reliability, correctness, and performance of data systems that feed performance analysis and decision-making.

The position is production-facing and collaborates with the Performance team to ensure data workflows are robust, observable, and efficient. Strong Python, PySpark, and Pandas skills are essential, with experience in production ETL environments.