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Lead cross-functional programs to build data pipelines, AI-powered tools, and dashboards that turn operational data into actionable insights for Oracle’s cloud infrastructure delivery teams.
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 & 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
Problem Solving
Communication & Influence
This is a full-time onsite role in Nashville, TN.
Career Level - IC4
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