Our Client is a leading commodity trading and investment firm. They are building out a high end data science platform which is essential to the core investment platform.
The role is crucial to implement new data management platforms, source new data sets and create new data ingestion. This position works with all aspects of data and will have significant exposure to the Risk and commercial investing teams globally.
- Complete data management and data architecture projects for new and existing data sources.
- Assist in transitioning existing databases, data sets and code to a new tech stack
- Use a variety of techniques including machine learning to lead analysis of data sets over time
- Manage end to end data ingestion process and publishing to investing teams
- Map, Standardise and normalise data
- Research project topics such as vendor trends, usage best practices, AI, Big Data, Vendors, etc.
- Assist in transitioning existing data sets, data bases and code to a new tech stack
- Create data quality analysis that identifies larger issues in data and assess data loads for tactical errors while building out appropriate work flows
- Capture changes in data input proactively and actively manage vendors
- Resolve and prioritise data issues based on business usage
- help with managing strategic initiatives regarding big data projects for the commercial (trading) business
- Collaborate with commercial teams to gain a better understanding of data architecture, data flow, investment process and gather functional requirements
- Asses gaps in current data sets and fix any issues
- 5+ years as a Data Engineer working with complex databases preferably in financial services or energy commodities
- Bachelor's degree in Mathematics, Physics, Computer Science, Business Intelligence or related field of study
- Experience working with data warehouse / relational data base
- Hands-on Snowflake experience strongly preferred