Vice President, Data Engineer

Castleton Commodities Management Services LLC has an opening for a Vice President, Data Engineer in Stamford, Connecticut.

The position duties are as follows: Play an integral role in the implementation of new data management platforms, create new data ingestion pipelines, and source new data sets. Assists with all aspects of data – from data architecture design to on-going data management, with significant exposure to Castleton risk and commercial investing teams globally. Daily job duties include:

• Execute data architecture and data management projects for both new and existing data sources, and help transition existing data sets, databases, and code to a new technology stack;
• Over time, lead analysis of data sets using techniques such as machine learning;
• Manage end to end data ingestion process and publishing to investing teams;
• Own the process of mapping, standardizing, and normalizing data;
• Perform ad hoc research on project topics such as vendor trends, usage best practices, big data trends, artificial intelligence, and vendors;
• Assess data loads for tactical errors and build out appropriate workflows, as well as create data quality analysis to identify larger issues in data;
• Actively manage vendors and capture changes in data input proactively;
• Prioritize and resolve data issues based on business usage;
• Assist with managing strategic initiatives around big data projects for the commercial (trading) business;
• Partner with commercial teams to gain understanding of current data flow, data architecture, and investment process as well as gather functional requirements;
• Collaborate with quantitative analysts and traders to develop and back test trading strategies using historical and real-time data; and
• Stay up to date on emerging technologies, tools, and trends in commodities trading and data engineering to drive innovation and continuous improvement.

The position requires a Bachelor’s degree in Computer Science, Mathematics, Engineering, Business Intelligence, a related field or foreign equivalent, followed by 5 years of progressively responsible experience as a Data Engineer. Experience must include:

3 years of experience with auto scalable, distributed databases in financial services or energy commodities, including experience with multi user support, and handling structured, semi structured, unstructured datasets; 3 years of experience with ETL/ELT frameworks; 3 years of experience with writing highly optimized SQLs; 3 years of experience with relational databases, including Snowflake or Oracle; 3 years of Python experience with Pandas, Numpy, and Scikit; and 1 year of experience with Power BI and Tableau.

Resumes to GBL-recruiting@cci.com, Ref. MA1