Data Engineer, Industrials L/S Equities - London

Balyasny Asset Management is looking for an exceptional data engineer would must have experience in a Data Engineering role already in either other funds/ banks to work with an Industrials portfolio team in London on projects related to infrastructure management, data analysis and data-driven idea generation. We are looking for someone with expertise in Data Engineering & Data Analytics who is interested in applying their skillset to a markets facing role. This is an excellent opportunity to take full ownership of a fundamental investment team’s data pipeline at a leading hedge fund, offering hands-on experience to work at the intersection of data analysis and investing.

Key Responsibilities

• Collaborate with Analysts and Portfolio Manager to develop creative uses for data in the investment process
• Collect structured and unstructured data from various sources (e.g., websites, PDF documents, e-mails, etc.), clean, transform and store this data in a format and in a storage location that ease the consumption of this data for analysis (e.g., Excel)
• Identify opportunities to improve existing infrastructure, such as optimizing data storage solutions or streamlining the data ingestion process to increase the volume, velocity, and variety of the ingested data
• Develop and expand team data infrastructure to capture new data streams and automate the end-to-end ETL/ELT process
• Support investment decisions through independent research on various new datasets, pinpointing trends, correlations, and patterns in complex datasets
• Effectively communicate technical details and insights to non-technical team members
• Take complete ownership of data pipeline as a fully integrated member of the team

Must have

• Bachelor’s or master’s degree in computer science, Mathematics, Physics or quantitative field from top schools
• Prior training in a quantitative scientific field that uses computational data analysis (e.g., computer science, statistics, applied mathematics, physics, engineering, economics/econometrics, chemistry/biology)
• 1 to 5 years of experience in building and managing ETL/ELT data pipelines
• Proficient in Python3 with a strong focus on the most common data libraries (e.g., pandas, NumPy) and SQL
• Experience with Apache Airflow for workflow management
• Proficient with Microsoft Excel
• Knowledge of the Amazon AWS data ecosystem
• Expertise in setting up, maintaining and fine-tuning SQL databases (e.g., PostgreSQL and Snowflake)
• Excellent communication skills, with the ability to explain technical concepts to non-technical users
• Attention to detail and exceptionally motivated, hard-working, and a self-starter combined with the highest integrity and character

Nice to Have

• Experience with data visualization tools such as Tableau or Streamlit
• Experience with Docker and containerized architectures (e.g., Kubernetes, AWS ECS)
• Experience with real-time data-streaming e.g. Kafka
• Experience with GitHub and Jenkins
• Basic understanding of markets and financial statements

Only apply if your profile fits the listed requirements. Please understand that we have a large volume of applicants and cannot reply to each one. Thanks for your interest in Balyasny. If your profile is suitable, we will reach out.

• Bachelor’s or master’s degree in computer science, Mathematics, Physics or quantitative field from top schools
• Prior training in a quantitative scientific field that uses computational data analysis (e.g., computer science, statistics, applied mathematics, physics, engineering, economics/econometrics, chemistry/biology)
• 1 to 5 years of experience in building and managing ETL/ELT data pipelines
• Proficient in Python3 with a strong focus on the most common data libraries (e.g., pandas, NumPy) and SQL
• Experience with Apache Airflow for workflow management
• Proficient with Microsoft Excel
• Knowledge of the Amazon AWS data ecosystem
• Expertise in setting up, maintaining and fine-tuning SQL databases (e.g., PostgreSQL and Snowflake)
• Excellent communication skills, with the ability to explain technical concepts to non-technical users
• Attention to detail and exceptionally motivated, hard-working, and a self-starter combined with the highest integrity and character, * Experience with data visualization tools such as Tableau or Streamlit
• Experience with Docker and containerized architectures (e.g., Kubernetes, AWS ECS)
• Experience with real-time data-streaming e.g. Kafka
• Experience with GitHub and Jenkins
• Basic understanding of markets and financial statements