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Our Client is a leading private equity firm with a portfolio of upstream gas production companies. By combining petroleum engineering expertise with advanced data analytics, artificial intelligence (AI), and machine learning (ML), Our Client is driving the digital transformation of upstream operations. With a diverse set of assets and a strong focus on innovation, this role provides the opportunity to shape the future of gas production and forecasting through cutting-edge technology.
About the Role The Petroleum Data Engineer will play a critical role in leveraging data to solve complex engineering challenges, optimize production, and drive operational efficiency across portfolio companies. This individual will build innovative data products, develop and deploy AI/ML models, automate workflows, and collaborate with engineering teams to unlock new insights. The role is ideal for a professional passionate about merging petroleum engineering expertise with modern data science to deliver measurable business impact.
Responsibilities
Develop, optimize, and maintain data pipelines to automate upstream gas production and forecasting workflows
Implement scalable data solutions to support monitoring, reservoir management, and efficiency initiatives
Integrate structured and unstructured data from sensors, logs, and well data into production systems
Design and deploy AI/ML models for production forecasting, reservoir simulation, and failure prediction
Analyze historical and real-time production data to identify trends and optimization opportunities
Collaborate with domain experts to align AI/ML models with engineering principles and field use cases
Build and deploy data products in partnership with digital and engineering teams across portfolio companies
Serve as a technical advisor to portfolio companies on data analytics and digital transformation initiatives
Develop user-friendly dashboards and interfaces for data visualization and stakeholder engagement
Ensure data quality, accuracy, and consistency across all pipelines and products
Implement governance policies to secure sensitive production data and meet industry regulations
Stay current with emerging technologies in petroleum data analytics, AI, and ML to drive innovation
Qualifications
Bachelor’s, Master’s, or PhD in Petroleum Engineering, Data Science, Computer Science, or related field
Five or more years of experience in upstream oil and gas, with a focus on gas production and forecasting
Proven track record applying AI and ML to solve petroleum engineering challenges
Proficiency in Python, R, or similar programming languages for data analytics and ML
Hands-on experience with frameworks such as TensorFlow, PyTorch, or scikit-learn
Strong understanding of upstream workflows, including reservoir simulation and optimization
Experience with cloud platforms such as Azure, AWS, or Google Cloud, and tools like Databricks or Synapse
Ability to build dashboards and visualizations using Power BI, Spotfire, or similar platforms
Preferred Qualifications
Knowledge of digital oilfield technologies, IoT integration, and real-time data processing
Experience with data governance frameworks and tools such as Microsoft Purview
Familiarity with industry datasets and platforms including Enverus or IHS
Soft Skills
Strong problem-solving abilities and innovative mindset
Excellent communication skills, with the ability to explain technical concepts to non-technical stakeholders
Collaborative approach to working across diverse teams and organizations
What you will achieve
Deliver data-driven solutions that optimize gas production and forecasting across portfolio companies
Enable portfolio companies to adopt AI/ML and advanced analytics as a competitive advantage
Contribute to the digital transformation of upstream operations, shaping the future of the energy industry
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Information Technology
Industries
Venture Capital and Private Equity Principals
#J-18808-Ljbffr
About the Role The Petroleum Data Engineer will play a critical role in leveraging data to solve complex engineering challenges, optimize production, and drive operational efficiency across portfolio companies. This individual will build innovative data products, develop and deploy AI/ML models, automate workflows, and collaborate with engineering teams to unlock new insights. The role is ideal for a professional passionate about merging petroleum engineering expertise with modern data science to deliver measurable business impact.
Responsibilities
Develop, optimize, and maintain data pipelines to automate upstream gas production and forecasting workflows
Implement scalable data solutions to support monitoring, reservoir management, and efficiency initiatives
Integrate structured and unstructured data from sensors, logs, and well data into production systems
Design and deploy AI/ML models for production forecasting, reservoir simulation, and failure prediction
Analyze historical and real-time production data to identify trends and optimization opportunities
Collaborate with domain experts to align AI/ML models with engineering principles and field use cases
Build and deploy data products in partnership with digital and engineering teams across portfolio companies
Serve as a technical advisor to portfolio companies on data analytics and digital transformation initiatives
Develop user-friendly dashboards and interfaces for data visualization and stakeholder engagement
Ensure data quality, accuracy, and consistency across all pipelines and products
Implement governance policies to secure sensitive production data and meet industry regulations
Stay current with emerging technologies in petroleum data analytics, AI, and ML to drive innovation
Qualifications
Bachelor’s, Master’s, or PhD in Petroleum Engineering, Data Science, Computer Science, or related field
Five or more years of experience in upstream oil and gas, with a focus on gas production and forecasting
Proven track record applying AI and ML to solve petroleum engineering challenges
Proficiency in Python, R, or similar programming languages for data analytics and ML
Hands-on experience with frameworks such as TensorFlow, PyTorch, or scikit-learn
Strong understanding of upstream workflows, including reservoir simulation and optimization
Experience with cloud platforms such as Azure, AWS, or Google Cloud, and tools like Databricks or Synapse
Ability to build dashboards and visualizations using Power BI, Spotfire, or similar platforms
Preferred Qualifications
Knowledge of digital oilfield technologies, IoT integration, and real-time data processing
Experience with data governance frameworks and tools such as Microsoft Purview
Familiarity with industry datasets and platforms including Enverus or IHS
Soft Skills
Strong problem-solving abilities and innovative mindset
Excellent communication skills, with the ability to explain technical concepts to non-technical stakeholders
Collaborative approach to working across diverse teams and organizations
What you will achieve
Deliver data-driven solutions that optimize gas production and forecasting across portfolio companies
Enable portfolio companies to adopt AI/ML and advanced analytics as a competitive advantage
Contribute to the digital transformation of upstream operations, shaping the future of the energy industry
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Information Technology
Industries
Venture Capital and Private Equity Principals
#J-18808-Ljbffr