Data Engineer

Fintal Partners; Chicago (IL); On-site; USD 120,000 - 180,000; Full time

Job summary

Fintal Partners in Chicago is seeking an experienced Data Platform Engineer to design and build scalable real-time and batch data infrastructure. You will partner with software engineers, quantitative researchers, and infrastructure teams to deliver robust data pipelines and analytics capabilities.

The role focuses on improving performance, reliability, and observability of production data systems, while shaping data architecture and ingestion strategies for large-scale markets data and trading

Qualifications

• Experience building production data platforms in distributed environments.
• Experience with real-time streaming and batch data pipelines.
• Strong programming skills in Python, Java, or SQL.
• Familiarity with modern data storage technologies (Iceberg, Databricks, S3, HDFS).
• Knowledge of Kubernetes, Docker, and cloud-native infrastructure.
• Solid Linux production operations understanding.
• Strong analytical mindset for data issue resolution.

Responsibilities

• 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.
• Collaborate with software engineers and researchers to optimize data architecture, storage, and ingestion strategies.
• Troubleshoot production issues and drive long-term platform stability improvements.
• Contribute to the evolution of the firm’s data ecosystem and engineering best practices.

Skills

Distributed data platforms

Kafka

Spark

Flink

Python

Java

SQL

Iceberg

Databricks

S3

HDFS

Kubernetes

Docker

Linux

Tools

Kafka

Spark

Flink

Iceberg

Databricks

S3

HDFS

Kubernetes

Docker

Job description

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