Data Production Engineer
Posted on 7/19/2023
INACTIVE
Develops automated trading algorithms using advanced mathematics
Company Overview
Hudson River Trading (HRT) stands out as a leading quantitative trading firm, employing over 800 experts from diverse disciplines, and providing liquidity on global markets with its advanced computing environment for research, development, and risk management. The company's culture fosters critical thinking and automation, with a strong commitment to ethical practices, advocating for fair and transparent markets. HRT's technical prowess and mathematical approach to trading, coupled with its industry leadership in algorithmic trading, make it an exceptional place to work for those seeking to impact the financial markets through technology.
Quantitative Finance
Financial Services
Data & Analytics
Company Stage
N/A
Total Funding
$225M
Founded
2002
Headquarters
New York, New York
Growth & Insights
Headcount
6 month growth
↑ 0%1 year growth
↑ 7%2 year growth
↑ 64%Locations
London, UK
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Data Analysis
Data Science
Linux/Unix
MySQL
Postgres
SQL
Python
CategoriesNew
Data & Analytics
Software Engineering
Quantitative Finance
Requirements
- Track record of being detail-oriented and thorough
- You excel in problem solving and researching large datasets to resolve complex issues
- You have a collaborative attitude that lends itself to cross-team customers and projects
- You thrive in the fast-paced environment of a daily live trading operation
- 2+ years of experience in a data engineering/science role OR a degree in data science or a similar discipline
- Experience in Python strongly preferred
- Experience with financial datasets (e.g. Refinitiv, S&P, Bloomberg) is a big plus
- Comfortable with the Linux command line
- Experienced in at least one SQL dialect (PostgreSQL, MSSQL, MYSQL) and able to use others as needed
- Able to provide technical support in a production trading environment
Responsibilities
- Data Engineering: Write tools to classify, onboard, and reconcile data. Onboard datasets, explore data, and automate tasks using a modern Python data stack
- Data Analysis: Parse, analyze, and understand data sets. Perform data reconciliations, validations, and quality checks. Identify and develop new processes within the data request process to enrich data. Assist our researchers in cleaning and featurizing data
- Data Debugging: Find anomalies in derived datasets and trace the issues back to their source. This can include using a mix of deductive reasoning, technical analysis, and communicating with multiple stakeholders in a data pipeline
- Production Support: Provide proactive oversight of our data pipeline, handle inquiries from internal customers, and resolve issues under efficient turnaround times
Desired Qualifications
- Experience managing ETL pipelines is a plus