Markets-Facing Data Engineer: End-to-End ETL & Analytics

Balyasny Asset Management L.P.; Greater London; On-site; GBP 60,000 - 80,000; Full time

Job summary

A leading hedge fund in Greater London is seeking a Data Engineer to join their Industrials portfolio team. This role involves developing data pipelines and infrastructure, supporting investment decisions through robust data analysis, and communicating insights effectively within a technical team. Ideal candidates will have a strong background in data engineering, 1 to 5 years of relevant experience, and proficiency in Python, SQL, and data management tools. This is a key opportunity to significantly impact the investment process.

Qualifications

• 1 to 5 years of experience in building and managing ETL/ELT data pipelines.
• Experience in computational data analysis and quantitative scientific fields.
• Ability to explain technical concepts to non-technical users.

Responsibilities

• Collaborate with Analysts and Portfolio Manager to develop creative uses for data.
• Collect and clean structured and unstructured data from various sources.
• Identify opportunities to improve existing infrastructure.
• Develop and expand team data infrastructure for new data streams.
• Support investment decisions through independent research on data trends.

Skills

Python3 proficiency

Expertise in data libraries (e.g., pandas, NumPy)

SQL knowledge

Excellent communication skills

Attention to detail

Education

Bachelor’s or master’s degree in computer science, Mathematics, Physics or a quantitative field

Tools

Apache Airflow

Microsoft Excel

AWS data ecosystem

SQL databases (e.g., PostgreSQL, Snowflake)

Data visualization tools (e.g., Tableau, Streamlit)

Job description

A leading hedge fund in Greater London is seeking a Data Engineer to join their Industrials portfolio team. This role involves developing data pipelines and infrastructure, supporting investment decisions through robust data analysis, and communicating insights effectively within a technical team. Ideal candidates will have a strong background in data engineering, 1 to 5 years of relevant experience, and proficiency in Python, SQL, and data management tools. This is a key opportunity to significantly impact the investment process.