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# Senior Engineer - Data Ingestion

- **Company:** Chicago Trading Company
- **Location:** United States
- **Experience:** Expert
- **Salary:** $200,000.0 - $250,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Microsoft Azure, C++ (Programming Language), Data Infrastructure, Python (Programming Language), Object-Oriented Software Development, Software Architecture, DataOps, SQL Databases, Systems Architecture, Google Cloud, High Performance Computing, Data Ingestion, Apache Spark, Build Tools, Data Pipelines
- **Published:** September 3, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=87baf9742099d6a3

## About the Role

* Hands-on experience building and operating large-scale data pipelines, ideally in the hundreds of terabytes to petabytes range.
 * Strong software architecture and large-scale system design skills.
 * Strong proficiency in SQL and in object-oriented languages such as Python.
 * Hands-on experience with at least one major cloud provider (AWS, Azure, GCP) and/or HPC workloads.
 * Strong interpersonal skills and the ability to work in a team environment.

NICE TO HAVE

 * Experience with tick capture, market data, or trading industry data (options, equities, futures).
 * C++.
 * Experience with data observability and data quality tooling, including diagnosing source data problems.
 * Experience with open table formats such as Iceberg or Delta, and with query engines such as Trino, Spark, or DuckDB.

## Description

* Own the quality, reliability, and overall health of our source data pipelines.
 * Work closely with Traders and Quantitative Researchers to understand their needs, and how they use our final data products.
 * Act as the data-delivery expert for your stakeholders, and design the most reliable and efficient way to source the data they need.
 * Optimize existing pipelines to improve SLA for users and lower the compute and storage footprint across the firm.
 * Migrate existing pipelines onto modern data platforms and hardware, and improve the process for future migrations.
 * Collaborate with the broader data organization to improve our overall platform offering and functionality.
 * Detect source data quality issues that lead to incorrect downstream metrics, and partner with data owners to build tools that surface and resolve these issues before users see them.


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