Data Engineer - Trading

Expand Energy Corporation • Spring, TX

40d

About The Position

Our core values — Stewardship, Character, Collaborate, Learn, Disrupt — are the lens through which we evaluate every business decision. As a dynamic, growing company that offers extremely competitive compensation and benefits, our employees are our most valued assets and the foundation of Expand's performance among our E&P competitors.
We seek applicants from all backgrounds to ensure we get the best, most creative talent on our team. We realize that, historically, underrepresented groups feel the need to be 100% qualified in order to apply.
If you meet any combination of our requirements, we encourage you to apply. We strive to hire people from a wide variety of backgrounds, not just because it's the right thing to do, but because it makes our company stronger.
Job Summary The Data Engineer - Trading Enablement 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 models and solutions 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 collaborate closely with data scientists and traders while having the autonomy to move quickly and define best practices. We operate strategically in collaboration with our IT teams, while serving as "special forces" for bespoke, short lead-time data needs.

Requirements

• Experience with Snowflake cloud data platforms, Python/Pandas, SQL, and orchestration tools (Airflow, dbt)
• Experience with diverse data integration methods including Snowflake data sharing, REST APIs, SFTP/FTP, web scraping, and automation scripting
• Proficient in PowerBI or similar front-end visualization tools for energy market analysis
• 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
• Proven ability to work effectively with business stakeholders, understand requirements quickly, and translate business needs into technical solutions
• Minimum: High school diploma or GED
• Minimum: 2 - 5 years related work experience

Nice To Haves

• Preferred: Bachelor's degree - from accredited university - IT, MIS, Computer Science, Engineering or related field
• Preferred: Experience in data engineering for energy commodities (natural gas/NGL, power markets, crude oil, LNG, or related markets)
• 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, oil & gas companies, or related commercially-oriented energy organizations
• Real-Time Data: Experience with streaming data and low-latency requirements for trading applications
• Leadership Experience: Track record of building, operating, and supporting performant databases and data pipelines

Responsibilities

• Design, implement, and manage 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
• Design, develop, and maintain data pipelines and models across internal and external datasets for marketing and trading solutions
• Apply understanding of technology and 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
• 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
• Develop and maintain data quality frameworks and validation processes critical for trading decisions
• Share knowledge with team members and help establish best practices for data engineering initiatives

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: High school or GED