Data Engineer - New York, United States - Walsh Employment
Description
PLEASE DO NOT APPLY FOR THIS ROLE IF YOU HAVE HAD MORE THAN 4 ROLES IN THE LAST 10 YEARS.
Our client is a leading quantitative investment company with a focus on computer-driven trading for global financial markets. They company harnesses the power of data and advanced technologies to drive innovative strategies and superior investment returns. We are now seeking an exceptional Data Engineer to join their busy, growing, and successful team.
Data Engineer
Manhattan, NY – hybrid model with 1 day per week working remotely.
Relocation assistance offered.
US citizenship or Green Card holder as well as transfer of a current H-1B Visa is also available if required.
c$300-$450K package with salary and compensation being flexible, competitive, and commensurate with experience and qualifications.
To be successful in this role:
You will be a confident Data Engineer with strong programming skills, including deep expertise in Python programming language, and you will have gained a Bachelor's degree or higher in Computer Science, Data Science, Engineering, or a related field. Other requirements for this role include:
Experience with data processing frameworks and tools such as Apache Spark, Hadoop, or similar, ideally within the context of financial markets, although this is not essential
Proficiency in SQL and database management systems (e.g., PostgreSQL, MySQL, or similar), with experience in high-frequency trading environments preferred
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform, and their application in quantitative finance
Excellent problem-solving skills and a creative approach to data engineering challenges in the context of quantitative trading
Strong communication and collaboration skills, with the ability to work effectively in a fast-paced, team-oriented environment
While a background in finance is beneficial, it is not mandatory
Job role and responsibilities:
As a Data Engineer you will play a critical role in data-driven initiatives, working on diverse projects that involve processing, analyzing, and interpreting large datasets within the context of global financial markets. You will have a strong programming background, particularly in Python, and a genuine enthusiasm for working with data. Other requirements for this role include:
Data Processing: Design and develop data pipelines to ingest, transform, and load large volumes of financial data from various sources, ensuring efficiency and scalability
Data Analysis: Perform exploratory data analysis to uncover insights and patterns within financial datasets, utilizing statistical methods and machine learning techniques
Programming: Write clean, efficient, and maintainable code in Python to implement data solutions and algorithms tailored to the needs of quantitative trading strategies
Database Management: Manage databases and data warehouses, optimizing performance and ensuring data integrity in the context of high-frequency trading systems
Data Visualization: Create compelling visualizations and dashboards to communicate findings and insights to traders and portfolio managers effectively
Collaboration: Collaborate with cross-functional teams, including quantitative researchers, traders, and technologists, to understand requirements and deliver data solutions that support investment strategies
Continuous Improvement: Stay updated on emerging technologies, tools, and best practices in data engineering within the financial industry, continuously seeking ways to improve processes and enhance efficiency