Senior Data Engineer - Trading Data & Real-Time Analytics

Belvedere Trading, LLC; Chicago (IL); On-site; USD 150,000 - 200,000; Full time

Benefits offered by this job

Discretionary bonuses

Benefits package

Job summary

Belvedere Trading, a leading proprietary trading firm headquartered in downtown Chicago, is seeking a Senior Data Engineer to work directly with trading desks to improve trading performance through robust data solutions.

You will design scalable data architectures, implement ETL pipelines, ensure data quality, and communicate across teams to translate analytic needs into reliable systems that support timely trading decisions.

Qualifications

• Experience designing and developing big data warehouses and ETL pipelines.
• Proven knowledge of SQL and Python.
• Navigate and integrate data across RDBMS, NoSQL, and Time Series.
• Experience with real-time messaging systems (Kafka, Kinesis, Pulsar) and stream processing (Flink or Spark).
• Craft high-performance BigQuery queries and optimize for scale.
• Excellent verbal and written communication, analytical and problem-solving skills.

Responsibilities

• Understand analytic needs to improve trading performance with traders.
• Design and maintain a modular data architecture to facilitate and scale future analysis.
• Ensure high data quality for all analytical trading datasets.
• Enforce data and visual standards, including modular design, testing, and documentation.
• Ensure technical solutions are simple and scalable for future use cases.
• Collaborate with on-desk staff and teammates to translate requirements into robust data solutions.

Skills

SQL

Python

BigQuery

Data integration

Analytical thinking

Communication

Tools

Kafka

Kinesis

Pulsar

Flink

Spark

NoSQL

Time Series

Job description

Belvedere Trading, a leading proprietary trading firm headquartered in downtown Chicago, is seeking a Senior Data Engineer to work directly with trading desks to improve trading performance through robust data solutions.

You will design scalable data architectures, implement ETL pipelines, ensure data quality, and communicate across teams to translate analytic needs into reliable systems that support timely trading decisions.