Data Operations Engineer - Remote

Overview

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform.

WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement.

Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.

The Role:

We are seeking a Data Operations Engineer to improve the reliability and performance of WorldQuant's data pipeline. Successful candidates will work with researchers, data strategists, operations and engineering teams to establish the smooth functioning of the pipeline sourced from an enormous and continuously updating catalog of vendor and market data.

What You’ll Do:

• Support the daily operation and monitoring of the pipeline.
• Triage issues by addressing urgent, real time trading alerts while also servicing research driven workflows.
• Improve the reliability and operability of pipeline components in a high velocity environment.
• Solve both business and technical problems around data structure, quality, and availability.
• Interface with external vendors on behalf of internal clients.

What You’ll Bring:

• Experience with the Unix platform and toolset such as bash, git, and regex.
• Fluency in one or more major programming languages like Python, Perl or C++ as well as common query languages like SQL and PromQL.
• Excellent English communication: Oral and Writing.
• Experience in the financial services industry or data science is a plus.
• The curiosity to dive into complex issues, find root causes, and suggest or implement solutions.
• A positive team focused attitude and work ethic.

Notes on schedule:

Please note that this role will periodically require coverage until 21:00 Uruguay time to bridge the gap with our Asia hours coverage. We also require light weekend coverage (rotated globally) during daytime hours. Flexible work from home hours are available.