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Principal Technical Program Manager – Data Intelligence, AI & Delivery Tooling (Nashville, TN)

Oracle

Principal Technical Program Manager – Data Intelligence, AI & Delivery Tooling (Nashville, TN)

full-timePosted: Aug 26, 2026Updated: Aug 27, 2026Nashville, TN, United States

Job Description

The Global Program Controls organization provides governance, reporting, controls processes, cost management support, and portfolio visibility to help Oracle Cloud Infrastructure deliver global data center programs with greater consistency, transparency, and execution discipline. We are seeking an experienced Technical Program Manager (TPM) to lead the development of data-driven tools, reporting platforms, and AI-enabled capabilities that improve the predictability, visibility, and operational excellence. This role is ideal for someone who combines strong technical skills in data engineering, analytics, automation, and Large Language Models (LLMs) with the ability to drive cross-functional programs from concept through production. Rather than managing infrastructure builds directly, this TPM will build the systems that enable delivery organizations to make faster, higher-confidence decisions.The successful candidate will partner with Engineering, Data Science, Data Center Delivery, Supply Chain, Network Deployment, Operations, and Product teams to create scalable solutions that transform operational data into actionable insights. Responsibilities:Data & AnalyticsDevelop scalable data pipelines that aggregate information from multiple enterprise systems into a trusted source of truth.Design and implement executive dashboards and reporting solutions that provide real-time visibility into delivery health, schedule performance, resource utilization, and risk.Define and maintain key performance indicators (KPIs) and delivery metrics that improve operational decision-making.Analyze large and complex datasets to identify trends, bottlenecks, risks, and opportunities for process improvement.Drive adoption of data-driven decision making across Data Center Delivery.AI & Large Language Models Identify and implement practical GenAI and LLM use cases that improve engineering productivity and operational efficiency.Design AI-powered assistants that help teams summarize project status, identify delivery risks, generate reports, and answer operational questions.Evaluate emerging AI technologies and recommend solutions appropriate for enterprise-scale deployment.Develop prompt engineering strategies and Retrieval-Augmented Generation (RAG) workflows that leverage internal operational data.Partner with security and governance teams to ensure responsible AI practices and data privacy compliance.Tool Development & Automation Lead the development of internal tools that automate manual processes and reduce operational overhead.Design integrations across enterprise platforms such as Jira, reporting systems, asset management tools, and data warehouses.Define technical requirements and work closely with software engineering teams to deliver scalable applications.Continuously identify opportunities to eliminate repetitive work through automation and workflow optimization.Technical Program Management Lead cross-functional initiatives involving Engineering, Data Engineering, Operations, Product Management, and Infrastructure teams.Translate business problems into technical roadmaps with clear milestones and measurable outcomes.Manage project plans, dependencies, risks, and stakeholder communications.Prioritize initiatives based on business impact and engineering capacity.Drive execution while maintaining alignment across multiple organizations.Continuous Improvement Establish metrics to measure tool adoption, operational efficiency, and business impact.Promote best practices for data quality, governance, documentation, and knowledge sharing.Champion a culture of experimentation, innovation, and continuous improvement.Preferred Qualifications Technical Skills Experience building data-intensive applications or internal engineering tools.Strong SQL skills and experience analyzing large datasets.Experience with Python or similar programming languages.Experience with APIs, automation frameworks, and system integrations.Experience building dashboards using Power BI, Tableau, Looker, or similar platforms.Familiarity with cloud-native architectures and distributed systems.AI & Data Experience implementing LLM or GenAI solutions in enterprise environments.Understanding of prompt engineering, vector databases, embeddings, and Retrieval-Augmented Generation (RAG).Experience working with structured and unstructured datasets.Knowledge of machine learning fundamentals and predictive analytics.Program Management Demonstrated success leading complex technical programs involving multiple stakeholders.Strong analytical and problem-solving skills.Excellent written and verbal communication skills.Ability to influence without direct authority.Preferred Experience Experience supporting cloud infrastructure or large-scale operational organizations.Experience developing executive reporting and operational dashboards.Experience improving business processes through automation.Familiarity with data center operations, infrastructure delivery, or cloud deployment lifecycle is a plus.Success in This RoleWithin the first year, the successful candidate will have: Built scalable reporting and analytics capabilities that become the trusted source for delivery metrics.Reduced manual reporting through automation and self-service tooling.Delivered AI-powered solutions that improve operational productivity.Established standardized KPIs for delivery health and execution.Improved leadership visibility into risks, dependencies, and delivery confidence.Increased organizational efficiency through modern data platforms and intelligent automation.Core Competencies Data Analysis & VisualizationTechnical Program ManagementAutomation & Workflow DesignAI / LLM ApplicationsData Engineering FundamentalsExecutive ReportingSystems ThinkingCross-functional LeadershipStakeholder ManagementProblem SolvingCommunication & Influence Disclaimer:Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements.Range and benefit information provided in this posting are specific to the stated locations onlyUS: Hiring Range in USD from: $102,300 to $209,500 per annum. May be eligible for bonus and equity.Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business.Candidates are typically placed into the range based on the preceding factors as well as internal peer equity.Oracle US offers a comprehensive benefits package which includes the following:1. Medical, dental, and vision insurance, including expert medical opinion2. Short term disability and long term disability3. Life insurance and AD&D4. Supplemental life insurance (Employee/Spouse/Child)5. Health care and dependent care Flexible Spending Accounts6. Pre-tax commuter and parking benefits7. 401(k) Savings and Investment Plan with company match8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week, the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for subsequent years of employment. Vacation accrual is prorated for employees working between 20 and 34 hours per week. Employees working fewer than 20 hours per week are not eligible for vacation.9. 11 paid holidays10. Paid sick leave: 72 hours of paid sick leave upon date of hire. Refreshes each calendar year. Unused balance will carry over each year up to a maximum cap of 112 hours.11. Paid parental leave12. Adoption assistance13. Employee Stock Purchase Plan14. Financial planning and group legal15. Voluntary benefits including auto, homeowner and pet insuranceThe role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted.Career Level - IC4

Locations

  • Nashville, TN, United States

Salary

102,300 - 209,500 USD / yearly

Responsibilities

  • Data & Analytics
  • Develop scalable data pipelines that aggregate information from multiple enterprise systems into a trusted source of truth.
  • Design and implement executive dashboards and reporting solutions that provide real-time visibility into delivery health, schedule performance, resource utilization, and risk.
  • Define and maintain key performance indicators (KPIs) and delivery metrics that improve operational decision-making.
  • Analyze large and complex datasets to identify trends, bottlenecks, risks, and opportunities for process improvement.
  • Drive adoption of data-driven decision making across Data Center Delivery.
  • Identify and implement practical GenAI and LLM use cases that improve engineering productivity and operational efficiency.
  • Design AI-powered assistants that help teams summarize project status, identify delivery risks, generate reports, and answer operational questions.
  • Evaluate emerging AI technologies and recommend solutions appropriate for enterprise-scale deployment.
  • Develop prompt engineering strategies and Retrieval-Augmented Generation (RAG) workflows that leverage internal operational data.
  • Partner with security and governance teams to ensure responsible AI practices and data privacy compliance.
  • Lead the development of internal tools that automate manual processes and reduce operational overhead.
  • Design integrations across enterprise platforms such as Jira, reporting systems, asset management tools, and data warehouses.
  • Define technical requirements and work closely with software engineering teams to deliver scalable applications.
  • Continuously identify opportunities to eliminate repetitive work through automation and workflow optimization.
  • Lead cross-functional initiatives involving Engineering, Data Engineering, Operations, Product Management, and Infrastructure teams.
  • Translate business problems into technical roadmaps with clear milestones and measurable outcomes.
  • Manage project plans, dependencies, risks, and stakeholder communications.
  • Prioritize initiatives based on business impact and engineering capacity.
  • Drive execution while maintaining alignment across multiple organizations.
  • Establish metrics to measure tool adoption, operational efficiency, and business impact.
  • Promote best practices for data quality, governance, documentation, and knowledge sharing.
  • Champion a culture of experimentation, innovation, and continuous improvement.
  • Experience building data-intensive applications or internal engineering tools.
  • Strong SQL skills and experience analyzing large datasets.
  • Experience with Python or similar programming languages.
  • Experience with APIs, automation frameworks, and system integrations.
  • Experience building dashboards using Power BI, Tableau, Looker, or similar platforms.
  • Familiarity with cloud-native architectures and distributed systems.
  • Experience implementing LLM or GenAI solutions in enterprise environments.
  • Understanding of prompt engineering, vector databases, embeddings, and Retrieval-Augmented Generation (RAG).
  • Experience working with structured and unstructured datasets.
  • Knowledge of machine learning fundamentals and predictive analytics.
  • Demonstrated success leading complex technical programs involving multiple stakeholders.
  • Strong analytical and problem-solving skills.
  • Excellent written and verbal communication skills.
  • Ability to influence without direct authority.
  • Experience supporting cloud infrastructure or large-scale operational organizations.
  • Experience developing executive reporting and operational dashboards.
  • Experience improving business processes through automation.
  • Familiarity with data center operations, infrastructure delivery, or cloud deployment lifecycle is a plus.
  • Built scalable reporting and analytics capabilities that become the trusted source for delivery metrics.
  • Reduced manual reporting through automation and self-service tooling.
  • Delivered AI-powered solutions that improve operational productivity.
  • Established standardized KPIs for delivery health and execution.
  • Improved leadership visibility into risks, dependencies, and delivery confidence.
  • Increased organizational efficiency through modern data platforms and intelligent automation.
  • Data Analysis & Visualization
  • Technical Program Management
  • Automation & Workflow Design
  • AI / LLM Applications
  • Data Engineering Fundamentals
  • Executive Reporting
  • Systems Thinking
  • Cross-functional Leadership
  • Stakeholder Management
  • Communication & Influence

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