Summary
✨ AI‑Generated
Lead the design and rollout of a large-scale Big Data platform in a fast-moving financial technology environment. You will build and monitor data pipelines, develop streaming applications, work with Java, Python, SQL, Spark and Flink, contribute to data modeling and capacity planning, and act as a trusted Big Data advisor to engineers and users. The role is based in an office environment.
Highlights
Lead major Big Data platform initiatives and serve as a technical authority for data engineering. The role combines architecture, streaming, data pipelines, modeling, capacity planning, and close collaboration with engineering teams and users.
Description
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 planningWork with users to keep data accurate and accessibleServe 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 environment3+ years building Kafka streaming applications and/or managing Kafka clusters2+ years developing pipelines or applications on Big Data backends (S3, HDFS, Databricks, Iceberg, etc.)Experience with Apache Spark, Apache Flink or comparable toolsStrong Java, Python and SQL skillsFamiliarity with common data science toolkits, particularly Python-basedPractical experience with Kubernetes and DockerExposure to monitoring tools such as Prometheus/Grafana, Alert Manager, Alerta and OpsGenieSolid statistical analysis skillsProven troubleshooting and root-cause analysis abilityUnix 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.
