Ben Singleton - head of data eng 
Travis Dunlap - some parallels to peters role. different in that its focused on python package building and tool buildign than pipelines, ncie to have someone w more swe exp than a traditional pipeline building data eng 
tools - around time series dat and statical related things 
Jr Enginner 

someone whose a DS who wants to be an engineer 


Priority:
python 
Data Sci / stats or time series data 
 not technical standpoint - working directly for building tools for internal customers 
someone with a produc thinking background would be helpful 
prefer someone with exp w more modern tools (some folks have the hadoop or hive etc)
snowflake or dtabricks exp preferred 
start up background would be ideal
AWS to have 
ideal exp? 3 to 6 
NYC role 
Finance background a +
NC? 6 months max max. 
Alt Data vendors could bea good place to look
3 days onsite minimum 

sell of the role? Viking has had a research data team foor # of yrs. earlier phases building out data pipelines for DS and inv staff. Last few years we asked fom the DS shifted - instead of cc data we need to backtests htis data or need toanalyze this data in a certai nway can u help build analytics tools to accelater wofklows. building tools for DS - its more math and clsoer to the analsyis iteself (inv research). 

Interview process? 
still working on finalizing this 
6 to 8 total rds. a few technials - python and sql and then stats as a third one and then a few bheavioral. cutlrue rds. 



 

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 this position in New York City is $150,000 to $200,000. In addition to base salary, Viking employees may be eligible for other forms of compensation and benefits, such as a discretionary bonus, 100% coverage of medical and dental premiums, and paid lunches. Actual compensation for successful candidates will be individually determined based on multiple factors including, but not limited to, a candidate’s skill set, experience, education, and other qualifications. For more information on our benefits, please visit www.vikingglobal.com/life-at-viking/  

Viking is an equal opportunity employer. Questions about your candidacy and requests for reasonable accommodation in the recruitment process should be directed to recruiting@vikingglobal.com.