Senior Data Engineer

Fintal Partners; Chicago (IL); Sur place; USD 120 000 - 170 000; Plein temps

Résumé du poste

Fintal Partners, a globally recognized quantitative trading firm, is expanding its engineering team to build the data platform powering real-time analytics, ML, and production trading systems in Chicago. The role focuses on large-scale distributed data workflows and low-latency processing while collaborating with researchers, software engineers, and infrastructure teams.

You will design scalable pipelines, implement streaming stacks with Kafka/Spark/Flink, optimize storage with Iceberg and S3,

Qualifications

• Strong experience building production data platforms in distributed environments.
• Hands-on with streaming technologies (Kafka, Spark, Flink) and modern storage.
• Proficient in Python, Java, or SQL for data engineering tasks.

Responsabilités

• Design and build scalable data infrastructure supporting real-time and batch workloads.
• Develop streaming and distributed data pipelines using modern Big Data technologies.
• Improve performance, reliability, and observability across production data systems.
• Work with engineering teams to optimize data architecture, storage, and ingestion strategies.
• Troubleshoot production issues and drive long-term improvements to platform stability.
• Contribute to the evolution of the firm's data ecosystem and engineering best practices.

Connaissances

Kafka

Spark

Flink

Python

Java

SQL

Kubernetes

Docker

Cloud (AWS/GCP)

Outils

Iceberg

Databricks

S3

HDFS

Description du poste

Our client is a globally recognized quantitative trading firm investing heavily in the next generation of its data platform. As data volumes continue to grow across research and trading, they're expanding the engineering team responsible for building the infrastructure that powers real-time analytics, machine learning, and production trading systems.

This role offers the opportunity to work on large-scale distributed data platforms where reliability, performance, and scalability are critical. You'll partner closely with software engineers, quantitative researchers, and infrastructure teams to design systems that process enormous volumes of market and business data with minimal latency

What you'll

• Design and build scalable data infrastructure supporting real-time and batch workloads
• Develop streaming and distributed data pipelines using modern Big Data technologies
• Improve performance, reliability, and observability across production data systems
• Work with engineering teams to optimize data architecture, storage, and ingestion strategies
• Troubleshoot production issues and drive long-term improvements to platform stability
• Contribute to the evolution of the firm's data ecosystem and engineering best practices

Looking For

• Strong experience building production data platforms in distributed environments
• Hands-on experience with Kafka, Spark, Flink, or similar streaming technologies
• Strong programming skills in Python, Java, or SQL
• Experience working with modern data storage technologies (Iceberg, Databricks, S3, HDFS, etc.)
• Familiarity with Kubernetes, Docker, and cloud-native infrastructure
• Solid understanding of Linux environments and production operations
• Strong analytical mindset with the ability to investigate and resolve complex data issues