Data Engineer, Industrials L/S Equities - London

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

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.