Data Engineer
IMC · On-site
MeritLog read this listing from IMC's Greenhouse job board and last checked it on September 8, 2026.
Source: the employer's Greenhouse job board. Open the original listing for current details.
Job details
- Work model
- On-site
- Salary
- $175,000 – $225,000
- Location
- Chicago, United States
- Occupation
- Database Architects(O*NET 15-1243.00)
Hiring context
How this role compares at IMC
IMC has 176 live roles in MeritLog’s catalog across 10 job families, and 104 of them are in data & analytics. 0 of those listings publish a pay range, a disclosure rate of 0%.
IMC concentrates this hiring in:
Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.
What the role asks for
What they're asking for
- 5+ years experience working in a mature data engineering environmentExperience
- 3+ years of experience building Kafka streaming applications and/or maintaining Kafka clustersExperience
- 2+ years of experience building applications/pipelines with Big Data backends (S3, HDFS, Databricks, Iceberg, etc)Experience
- Experience with Apache Spark, Apache Flink or similar toolsSkill
- Strong Java, Python, and SQL development skillsSkill
- Experience with common data-science toolkits, especially python-basedSkill
- Hands-on experience with Kubernetes and DockerSkill
- Experience with monitoring tools such as Prometheus/Grafana, Alert Manager, Alerta and OpsGenieSkill
- Strong statistical analysis skillsSkill
- Demonstrated ability to troubleshoot and conduct root-cause analysisSkill
- Unix scripting experience (bash, python, etc.)Skill
Parsed by MeritLog from the employer’s own posting. The full description follows below.
Job description
We are seeking a dedicated and experienced Data Engineer to join our Chicago team. The ideal candidate is energized by working in a cutting-edge environment that enables IMC to continue to be at the forefront of the evolving global financial markets. Core Responsibilities • Architect, develop and deploy our Big Data environment (Kafka, Hadoop, Dremio, etc.) • Build, deploy, and monitor our data processing pipelines (Java, Python, Spark, Flink) • Collaborate with development teams on data modeling, data ingestion, and capacity planning • Work with users to ensure data integrity and availability • Act as a Big Data SME and consult on a variety of data-related questions from users and developers Skills and Experience: • 5+ years experience working in a mature data engineering environment • 3+ years of experience building Kafka streaming applications and/or maintaining Kafka clusters • 2+ years of experience building applications/pipelines with Big Data backends (S3, HDFS, Databricks, Iceberg, etc) • Experience with Apache Spark, Apache Flink or similar tools • Strong Java, Python, and SQL development skills • Experience with common data-science toolkits, especially python-based • Hands-on experience with Kubernetes and Docker • Experience with monitoring tools such as Prometheus/Grafana, Alert Manager, Alerta and OpsGenie • Strong statistical analysis skills • Demonstrated ability to troubleshoot and conduct root-cause analysis • Unix scripting experience (bash, python, etc.) #LI-DNP The Base Salary range for the role is included below. Base salary is only one component of total compensation; all full-time, permanent positions are eligible for a discretionary bonus and benefits, including paid leave and insurance. Please visit Benefits - US | IMC Trading for more comprehensive information. Salary Range $175,000-$225,000 USD About Us IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.