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# AI Engineer - Data Analytics & Visualization (Oil and Gas experience)

- **Company:** Red Oak Technologies, Inc.
- **Location:** Denver, CO, United States
- **Experience:** Expert
- **Salary:** $140,000.0 - $170,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Analytics Applications, Data Architecture, Data Validation, Information Engineering, Data Visualization, Operational Data Store, Power BI, Cloud Services, Unstructured Data, Google Cloud, Large Language Models, Snowflake, Generative AI, Information Technology, Data Analytics, Data Management, Claude, Virtual Agents, Spotfire, Model Context Protocol, GPT, Data Pipelines, Databricks
- **Published:** October 14, 2026
- **Apply:** https://www.adzuna.com/details/5927274066

## About the Role

This is a hands-on, business-facing technical role requiring strong communication skills, industry knowledge, and experience delivering practical data-driven solutions., * Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.

 * 5+ years of experience in data analytics, business intelligence, data engineering, digital transformation, or a related technical field.
 * Upstream oil and gas industry experience is required, including familiarity with drilling, reservoir, production, or related operations.
 * Hands-on experience building dashboards, data visualizations, reports, and business intelligence solutions.
 * Proficiency with Power BI, Spotfire, or comparable visualization platforms.
 * Experience with Databricks, Snowflake, Google Cloud data platforms, or similar cloud data warehouse technologies.
 * Strong understanding of data modeling, data pipelines, data orchestration, and modern data architecture.
 * Demonstrated ability to work directly with business stakeholders, gather requirements, and translate operational needs into technical solutions.
 * Strong analytical, problem-solving, communication, and collaboration skills.

Preferred Qualifications

 * Hands-on experience using Generative AI tools such as ChatGPT, Claude, or similar foundational models to improve analytics and business workflows.
 * Familiarity with Large Language Models (LLMs), LangChain, Model Context Protocol (MCP), and AI agent frameworks.
 * Experience developing AI-powered dashboards, intelligent assistants, or automated analytics workflows.
 * Background in petroleum engineering, reservoir engineering, drilling engineering, or upstream oil and gas operations.
 * Direct experience with Databricks and its data engineering and analytics capabilities.
 * Experience presenting analytics solutions to senior leadership and operational stakeholders., Interested candidates with upstream oil and gas experience and strong data analytics, visualization, and AI skills are encouraged to apply.

## Description

The ideal candidate will work directly with drilling, reservoir, engineering, and operations teams to understand business challenges and translate requirements into meaningful dashboards, reports, data models, and AI-enabled analytics solutions., * Collaborate with upstream oil and gas leadership, drilling, reservoir, and operations teams to understand business requirements and identify opportunities for AI and analytics solutions.

 * Design, develop, and maintain dashboards, reports, and data visualizations using Power BI, Spotfire, or similar BI platforms.
 * Translate complex operational data into actionable insights that support business decisions.
 * Develop AI-powered analytics tools, intelligent workflows, automated reporting, and data-driven solutions.
 * Build and optimize analytics-ready data models using Databricks, Snowflake, or comparable cloud data platforms.
 * Work with structured and unstructured data to support scalable AI and business intelligence applications.
 * Perform data quality checks, troubleshoot data pipelines, and ensure the accuracy and reliability of analytics outputs.
 * Partner with data engineering and technical teams to improve data accessibility, integration, and performance.
 * Research emerging AI technologies and recommend opportunities to improve business processes and operational efficiency.
 * Document technical processes and communicate findings to technical and nontechnical stakeholders.