Data Engineer – Data Science & Technology
Posted
Overview
In this role you will help build and evolve data platforms that empower front-office trading teams to understand markets, forecast prices, and manage risk. You will work within the Data Engineering team to design data architectures, ingest and normalize data, and support advanced analytics across commercial trading activities. You will collaborate with global investors and data users to improve data quality and enable scalable decision-making. This is a fast-paced role at the intersection of data and energy markets, offering a direct view of how data-driven tech shapes investment strategies.
Pay / Benefits- Competitive medical, dental, retirement and life insurance
- Employee assistance & wellness programs
- Parental and family leave policies
- Tuition assistance & reimbursement
- Continued learning opportunities
- Competitive paid time off
- Execute data architecture and data management projects for new and existing data sources
- Migrate data sets, databases, and code to a new technology stack
- Manage end-to-end data ingestion and publish data to investing teams
- Own data mapping, standardization, and normalization processes
- Conduct ad hoc research on topics like vendor trends, big data, and AI
- Assess data loads and build workflows; perform data quality analysis to identify issues
- Manage vendors and capture changes in data input proactively
- Prioritize and resolve data issues based on business usage
- Assist with strategic big data initiatives for the commercial/trading business
- Partner with commercial teams to understand data flow, architecture, and requirements
- Assess gaps in datasets and remediate
- Bachelor’s degree in Computer Science, Mathematics, Physics, Business Intelligence, or related field
- 3+ years of Data Engineering experience focusing on SQL, data architecture, and dimension modeling
- Experience with ETL/ELT frameworks to build large-scale pipelines
- Advanced SQL skills; experience with relational databases; Snowflake highly preferred
- Hands-on Python, Pandas, NumPy experience
- Ability to communicate with a range of data users from technical to non-technical
- Team player with execution focus in a fast-changing project environment
- Willingness to work in a high-intensity setting and outside normal hours when needed
- Experience in energy commodities or financial services is nice to have but not required
- communication
- team collaboration
- execution-focused
- SQL programming
- data architecture
- dimension modeling