About the Role

As a Data Engineer at a quantitative hedge fund, you will play a critical role in designing, building and maintaining the firm’s data infrastructure, which is a foundational component of our investment strategies. Your primary responsibilities will include identifying useful datasets, which could give us an informational advantage over other investors, and then collecting and processing those datasets. You will also develop data quality controls to ensure data accuracy and integrity, and you will work with software engineers to integrate the data infrastructure with other systems and applications.You will work closely with the investment team, data scientists, and software engineers to ensure that the data pipeline is optimized for performance, reliability, and scalability.

Beyond that, the PharVision team values self-awareness, intellectual curiosity, and a team-player mentality. You will be working side-by-side and learning from highly experienced investment professionals, softare engineers and quantitative researchers.

If you are passionate about leveraging technology to drive investment insights and thrive in a fast-paced, collaborative environment, we encourage you to apply for this exciting opportunity.

 

Responsibilities

• Design, build, and maintain the firm’s data infrastructure using Python, Pandas, Apache Airflow and other relevant tools
• Implement ETL processes to collect, clean, and transform data from a variety of sources
• Collaborate with the researchers to identify and evaluate datasets potentially useful to the investment process
• Optimize data processing pipelines for performance and scalability using AWS and other cloud technologies
• Develop data quality controls to ensure data accuracy and integrity
• Work with software engineers to integrate the data infrastructure with other systems and applications
• Stay up-to-date with the latest developments in data engineering and contribute to the development of best practices within the firm

 

Technical Requirements

• At least a graduate degree in a technical field
• Eagerness to learn about financial markets and ways to gain an informational advantage over the competition
• 5+ years of experience in data engineering or a related field
• Strong programming skills in Python and experience working with Pandas
• Experience with AWS or other cloud technologies
• Familiarity with data modeling and database design concepts
• Experience with ETL processes and tools
• Excellent problem-solving skills and attention to detail
• Strong communication skills and ability to work collaboratively in a team environment

Nice to Have

• KX / KDB+ / q experience
• Exposure to the Agile approach and methodology
• Experience or at least interest in machine learning techniques, time series analysis, and econometrics
• Experience in Deep Learning: DNN, CNN, RNN/LSTM, GAN, or other autoencoders
• Basic understanding of equity markets