Data Engineer

Viking Global Investors LP is a global investment firm founded in 1999. We manage more than $50 billion of capital for our investors across public equity, private equity, and credit and structured capital investment strategies. We have more than 275 employees and offices in Stamford, New York, Hong Kong, London, and San Francisco.

LOCATION: 660 Fifth Ave, New York, NY (in-person attendance required)  

JOB FUNCTION  

The Data Engineer is a member of the Investment Data Engineering team and is primarily responsible for developing analytical tools and Python packages that empower data scientists to efficiently analyze data. The role focuses on applying modern software engineering principles to design, build, and maintain reusable analytical frameworks that enhance the productivity of the data science team. The Data Engineer will collaborate with data scientists to understand their workflows, identify opportunities for automation, and implement solutions that streamline data processing and modeling tasks. This position requires a strong foundation in Python development, a background or interest in statistics and time series analysis, and a passion for creating intuitive, well-documented tools that accelerate investment research.  

RESPONSBILITIES  

Responsibilities may include, but are not limited to:  

• Design, develop, and maintain Python packages and analytical tools that enhance the efficiency of time series analysis workflows for the data science team  
• Collaborate with data scientists to translate their analytical needs into well-architected solutions  
• Implement automated testing, documentation, and CI/CD pipelines to ensure reliable code  
• Build intuitive APIs and interfaces that allow data scientists to easily conduct complex analyses  
• Develop tools that integrate with existing cloud infrastructure
• Support the team's data visualization capabilities in Tableau and promote best practices  
• Maintain tools that help data scientists programmatically leverage AI to augment analyses
• Assist in creating and maintaining data pipelines that ingest and transform critical datasets
• Participate in code reviews, architecture discussions, and conversations on software standards  
• Ensure timely delivery of projects and maintain clear communication with stakeholders  

QUALIFICATIONS  

The ideal candidate must have:  

• A minimum of 3 years of relevant work experience  
• A degree in computer science, statistics or a related field, with a record of academic success  
• Excellent computer science fundamentals and problem-solving skills, including understanding of object-oriented and functional programming principles
• Strong proficiency in Python (especially pandas and other data analysis libraries)  
• Experience creating and maintaining Python packages with proper documentation and testing  
• Experience with version control systems (Git) and collaborative development workflows  
• Familiarity with SQL in the context of a modern data warehouse (i.e. Snowflake, BigQuery etc.) 
• Experience working in Linux environments  

The ideal candidate will also have:  

• Experience with time series analysis and statistical methods  
• Experience with data visualization tools, particularly Tableau
• Familiarity with cloud ecosystems (AWS, Azure, GCP)
• Experience with CI/CD patterns, Docker, and containerization  
• Experience with pipeline orchestration tools (Dagster, Apache Airflow, Prefect)  
• Prior investment management or financial services industry experience  

The base salary range for