Data Software Engineer

Quantitative Trading Firm #015

Data is at the core of everything we do here at our firm. We excel at deriving deep insights from all types of data, allowing us to achieve consistent success in a competitive market. As we think about exciting new avenues for growth, we look forward to expanding the scope of data at our firm to new frontiers.

Being a Data Software Engineer at our firm means being a pioneer. In this role, you’ll have the opportunity to work on problems that are pretty brand new to us. You will help onboard and study alternative datasets for use in our trading strategies. You will help design tools, processes, and an entirely new system for managing, storing, accessing, and exploring data at our firm. Your work will unlock new areas of research, enable new insights and signals, and help us expand the footprint of our trading. We’re looking for someone who loves data (maybe even dreams about data) and wants to be a critical part of bringing a world-class data warehouse to life.


Partner and support our business users in their interactions with the data platform and ensure smooth delivery of data – from across the landscape of alternative, reference, financial, and market data across all asset classes
Evaluate, clean, and normalize data; perform initial quantitative analysis to assess suitability of data under trail and develop pipelines to automate processes
Pair up with Algo Developers to onboard and study alternative datasets for use in our trading strategies; revisit and enhance the data workflows around existing datasets to make research more productive; normalize key metrics across multiple data vendors
Work closely with financial and alternative data vendors, including Bloomberg, Refinitiv and many others, and navigate their various delivery platforms (FTP, APIs, etc)
Build tools and automation capabilities for our data pipeline in order to ensure the overall quality of our data platform
Design and implement our data storage strategy to help drive successful delivery and access of data in our data centers around the world


Strong programming experience in Python
Experience in numpy/pandas is a plus, but not required
Experience in at least one of the following:
Data infrastructure experience – you know how to really store data; and no, we don’t mean just knowing not to save an Excel file on your desktop (everyone knows that’s messy and it should be in a nicely named folder)
Experience managing ETL pipelines and working with financial data vendors and their various delivery methods
Experience in serving data in a large, distributed system
Experience working on financial datasets, such as fundamental, alternative, news or reference data (e.g. IBES, Refinitiv, Barra, Factset, Compustat)
Track record of working successfully in a collaborative environment
Top-notch communication skills


You have a minimum of 2-3 years of experience working in data infrastructure and/or with financial datasets
You possess a Bachelor’s degree in computer science, engineering, math or a related field
You may pride yourself about that dataset quirk nobody else understands (or knows about), and have automated or normalized a data processing pipeline or two
You enjoy being part of an amazing team but don’t mind working alone on a difficult problem
You can investigate and fix problems quickly
You really like to work with people who motivate you and make you better

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