Sr. Manager, Data Engineering at Helmerich & Payne in Tulsa-OK-USA

Job description

At H&P, our people are our strength. Since 1920, Helmerich and Payne has been the industry’s most trusted partner in drilling productivity and reliability. As the world changes, so does our approach. We are changing the landscape of drilling by using cutting-edge rig technologies and drilling solutions to build upon a century of success, all while continuing to deliver better outcomes for our customers. At H&P, our people are our strength. We strive to continually lead with our Core Values that enable employees to develop on their H&P Journey. We believe that doing the right thing means creating a more diverse, equitable, and inclusive workplace that empowers our people to bring their authentic selves to work every day. Some companies offer career paths. We offer a Journey of a Lifetime. Let's go far, together. Hear directly from our employees, and leaders about their unique journeys at Helmerich and Payne . Location: Tulsa Office Work Type: Onsite At a Glance: We are seeking a strategic Senior Manager, Data Engineering to own the strategy, delivery, and governance of our enterprise data platforms. This leader sets the direction for data warehouse, data lake, and lakehouse architecture, leads data engineering managers and teams across multiple locations, and partners with executive and business leaders to turn data into a trusted, reusable asset that powers business intelligence, operational reporting, and AI and machine learning across the organization. What you will do: Deliver a scalable and easily accessible data repository to power AI models, tools, and products. Surface data to AI through Model Context Protocol (MCP) servers, APIs, and other methods so AI tools can consume it natively and in the timeframe initiatives need. Establish these data models as the source of truth, in close alignment with Digital Operations and Digital Drilling Solutions. Define the scope of data, including type and age, required to surface and effectively build models, and ensure AI initiatives have the required data when they need it. Own and execute the enterprise data engineering strategy and multi-year roadmap, aligned to business and functional unit and IT priorities. Lead and develop a multi-team organization of data engineering managers, leads, ETL and BI developers, and data architects; build bench strength, skills, and succession across locations. Set architecture direction and standards for enterprise data lake, lakehouse, data warehouse, and cloud analytics platforms, and govern their adoption. Own the data platform investment: budget, capacity, and the vendor and managed-service-provider relationships that support it, partnering with Supply Chain, who executes negotiations. Establish and run enterprise data governance, quality, security, and master data management as a sustained program, not a one-time project. Deliver capabilities for trusted business intelligence, KPI dashboards, and self-service reporting on top of the enterprise data foundation. Lead major modernization and migration initiatives from legacy platforms to modern cloud ecosystems, and integrate ERP data (Oracle EBS, SAP, and others) into the analytics estate. Partner with executive and business stakeholders across Finance, Operations, Supply Chain, and IT to prioritize demand, set service levels, and measure the value delivered. Ensure operational excellence across the platform: reliability, performance, cost efficiency, and DataOps and CI/CD discipline. Enterprise ERP, Finance, and Industry Expertise Strong functional understanding of Finance, Accounting, Procurement, and Supply Chain business processes. Experience supporting enterprise ERP ecosystems (Oracle EBS, SAP, and Workday), including Oracle EBS modules (Financials, Procurement, Supply Chain, Inventory, Projects, and HR), and integrating ERP data into enterprise data warehouses and analytics platforms. Experience with oil and gas operational, drilling, production, and financial data environments, and upstr