Data Architect

5 days ago


Stamford, Connecticut, United States Castleton Commodities International Full time

Position Overview:

Castleton Commodities International is a leading global energy commodities merchant and infrastructure asset investor. Our company employs a proprietary approach in the physical and financial commodity markets, providing valuable market insights and access to our investors. As a strategic investor and developer, we leverage our market expertise, operations capabilities, and industry knowledge to invest in and develop select commodity infrastructure assets. This integrated platform has generated strong risk-adjusted returns for our investors since our formation.

The role of Data Architect - Energy Commodities will play an integral part in implementing new data management platforms, creating new data ingestion pipelines, and sourcing new data sets. This position will assist with all aspects of data, from data architecture design to ongoing data management. You will have significant exposure to our Risk and commercial investing teams globally.

  1. Execute data architecture and data management projects for both new and existing data sources.
  2. Help transition existing data sets, databases, and code to a new technology stack.
  3. Over time, lead analysis of data sets using various techniques, including machine learning.
  4. Manage end-to-end data ingestion process and publishing to investing teams.
  5. Own the process of mapping, standardizing, and normalizing data.
  6. Ad hoc research on project topics, such as vendor trends, usage best practices, big data trends, artificial intelligence, vendors, etc.
  7. Help transition existing data sets, databases, and code to a new technology stack.
  8. Assess data loads for tactical errors and build out appropriate workflows, as well as create data quality analysis that identifies larger issues in data.
  9. Actively manage vendors and capture changes in data input proactively.
  10. Properly prioritize and resolve data issues based on business usage.
  11. Assist with managing strategic initiatives around big data projects for the commercial (trading) business.
  12. Partner with commercial teams to gain understanding of current data flow, data architecture, investment process, as well as gather functional requirements.
  13. Assess gaps in current datasets and remediate.


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