Principal Data Engineer

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 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 Ops Genie 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.