Job Description
Job Summary
The Data Engineer - Energy Trading will be re-imagining and designing solutions tailored to the dynamic and market-driven needs of the Marketing & Commercial division (analysts, traders, originators and executive leadership). This role involves building robust data infrastructure across natural gas, LNGs, power, and related commodities while understanding the unique challenges of energy market data - from pipeline flows and storage dynamics to the explosion in AI-driven power demand. You'll work within our Fundamental & Quantitative Analytics team, collaborating closely with data scientists and traders while having the autonomy to move quickly and define best practices. We operate strategically to design commercial-focused data architecture in collaboration with our IT teams, while serving as "special forces" for bespoke, short lead-time data needs. Reporting structure within Fundamental & Quantitative Analytics team will be determined based on team composition and individual experience levels.
Job Duties & Responsibilities
- Design and implement data onboarding processes for diverse energy commodity datasets including gas flows, power generation, oil and gas production data, market pricing, weather, and other market fundamentals
- Build and maintain data pipelines across various integration methods including Snowflake data sharing, APIs, SFTP transfers, web scraping, and automation tools
- Work efficiently as part of Marketing & Commercial (analytics trading, origination) team, effectively coordinating with IT teams to rapidly onboard new datasets, and understand evolving business requirements
- Apply understanding of energy market data, commodity flows, and trading applications to optimize data models, integration approaches, and integrity checks/alerting, including developing robust processes and technical documentation
- Appropriately scope out projects and implement efficiently to meet requirements of commercial stakeholders (trading, analytics)
- Contribute to technical decision-making to balance speed and scalability with long-term objectives, ensuring data architecture supports current needs and future applications including AI/ML and LLM technologies
- Share knowledge with team members and help establish best practices for data engineering initiatives
- Develop and maintain data quality frameworks and validation processes critical for trading decisions
Job Specific Skills
- Solid understanding of energy commodity data characteristics and market structures, with demonstrated ability to quickly learn and work with stakeholders to address the unique challenges of integrating energy datasets
- Hands-on experience with diverse data integration methods including Snowflake data sharing, REST APIs, SFTP/FTP, web scraping, and automation scripting
- Expert-level experience with cloud data platforms (Snowflake preferred), Python/Pandas, SQL, and orchestration tools (Airflow, dbt)
- Proven ability to work effectively with business stakeholders, understand requirements quickly, and translate business needs into technical solutions
Education
Minimum: High school diploma or GED
Preferred: Bachelor’s degree - from accredited university - IT, MIS, Computer Science or related field
Experience
Minimum: 2 - 5 years related work experience
Preferred: 3+ years experience in data engineering with exposure to energy commodities (natural gas/NGL, power markets, crude oil, LNG, or related markets)
Additional Qualifications
- Natural Gas Market Experience: Experience with natural gas market data sources, pipeline flow data, storage reporting, and basis/location-specific pricing datasets. Candidates from adjacent energy markets with strong technical skills will be considered
- Energy Trading Background: Experience at energy trading firms, commodity companies, or related commercially-oriented energy organizations
- Cloud Platforms: Snowflake experience strongly preferred; AWS, Azure, or GCP experience with relevant services (Redshift, Lambda, S3, etc.)
- Real-Time Data: Experience with streaming data and low-latency requirements for trading applications
- Data Visualization: Experience with PowerBI, Spotfire, Tableau, or similar tools for energy market analysis
- Leadership Experience: Track record of leading technical projects and mentoring data engineering teams
- Vendor Management: Experience working with energy data vendors and managing complex data acquisition relationships