Engineer, Petroleum (Supply Appraisal)

Description

The Upstream Supply Appraisal team is seeking an experienced petroleum engineer who can evaluate future oil, natural gas, and NGL supply while developing practical, reproducible analytical solutions. The role applies Python, SQL, statistics, and AI-enabled development tools to strengthen forecasting, automate workflows, and translate complex upstream data into clear business insights. Responsibilities include but are not limited to:

• Develop production forecasts for producers, assets, acreage positions, and key U.S. producing regions in partnership with Commercial teams.
• Evaluate well performance, development activity, inventory, type curves, and basin trends affecting future oil, natural gas, and NGL supply.
• Support midstream capital projects and strategic evaluations across gathering, processing, pipelines, storage, fractionation, and exports.
• Build and automate analytical workflows using Python, SQL, applied statistics, and visualization tools.
• Use AI-assisted and agentic development tools to accelerate analysis, coding, research, and workflow automation, with appropriate validation and engineering judgment.
• Partner with Data Engineering, IT, AI, and Cybersecurity teams to move selected solutions into governed, supported production environments.
• Communicate findings and business implications to Commercial teams, Investor Relations, and senior management.

Qualifications

The successful candidate will meet the following qualifications:

• Bachelor's degree in Petroleum Engineering or another relevant STEM discipline.
• 3+ years of relevant oil and gas experience in petroleum, production, or reservoir engineering; reserves; forecasting; upstream analytics; or supply appraisal.
• Strong knowledge of key U.S. producing regions and the technical and economic drivers of upstream and midstream businesses.
• Working knowledge of applied statistics, uncertainty and sensitivity analysis, model validation, and large datasets.
• Strong written and verbal communication skills, including the ability to translate technical analysis into clear business insights.
• Experience developing reproducible analytical solutions using documentation, testing, and version control.
• Experience with AI-assisted or agentic development tools such as Claude Code, GitHub Copilot, or comparable platforms.
• Experience with Snowflake, Power BI, ArcGIS, Spotfire, cloud platforms, or similar data and visualization technologies.
• Demonstrated proficiency with Python and SQL for data analysis, automation, or analytical workflow development.