Principal Data Engineer

We're looking for an experienced, driven Principal Data Engineer to join our Chicago office. You'll do well here if you enjoy a fast-moving, innovative environment that keeps the firm at the leading edge of global financial markets.

What You'll Do

• Design, build and roll out our Big Data platform (Kafka, Hadoop, Dremio, etc.)
• Develop, deploy and monitor data processing pipelines (Java, Python, Spark, Flink)
• Partner with engineering teams on data modeling, ingestion and capacity planning
• Work with users to keep data accurate and accessible
• Serve as the go-to Big Data expert, advising users and developers on data questions

What You'll Bring

• 5+ years in an established data engineering environment
• 3+ years building Kafka streaming applications and/or managing Kafka clusters
• 2+ years developing pipelines or applications on Big Data backends (S3, HDFS, Databricks, Iceberg, etc.)
• Experience working in an "on-prem" / Linux environment is highly preferred
• Experience with Apache Spark, Apache Flink or comparable tools
• Strong Java, Python and SQL skills
• Familiarity with common data science toolkits, particularly Python-based
• Practical experience with Kubernetes and Docker
• Exposure to monitoring tools such as Prometheus/Grafana, Alert Manager, Alerta and OpsGenie
• Solid statistical analysis skills
• Proven troubleshooting and root-cause analysis ability
• Unix scripting experience (bash, Python, etc.)

About the Firm

Our client is a research-led proprietary trading firm where quant modeling, machine learning and engineering drive how markets are traded. A steady liquidity provider for over three decades, the firm trades across global venues, delivering strong value and risk outcomes for investors. It runs on its own capital and in-house technology, building proprietary systems and algorithms. Researchers, traders and engineers work as one team, using fast experimentation, advanced infrastructure and real-time feedback to turn ideas into execution and execution into an edge.