Sr. Manager, Data Engineering

Helmerich & Payne•Tulsa, OK

3d•Onsite

About The Position

Helmerich and Payne is seeking a strategic Senior Manager, Data Engineering to own the strategy, delivery, and governance of enterprise data platforms. The role sets 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 make data a trusted, reusable asset for business intelligence, operational reporting, and AI and machine learning. The role is based at the Tulsa Office and is onsite. The leader will deliver accessible, scalable data repositories and enable AI tools to consume governed data through MCP servers, APIs, and other methods. They will establish enterprise data engineering strategy and a multi-year roadmap, develop the organization, set architecture standards, own platform investment and vendor relationships, and establish enterprise programs for data governance, quality, security, and master data management. The position also leads business intelligence and self-service reporting capabilities, modernization and cloud migration initiatives, and the integration of ERP data into the analytics estate. The Senior Manager partners with stakeholders across Finance, Operations, Supply Chain, and IT to prioritize demand and measure value, while ensuring platform reliability, performance, cost efficiency, and disciplined DataOps and CI/CD practices. The role calls for strong enterprise ERP, finance, procurement, supply chain, and oil and gas domain knowledge, along with experience in modern data platforms and analytics. Microsoft Fabric experience is emphasized, including its Lakehouse, Warehouse, Data Factory, Real-Time Analytics, OneLake, governance, security, and integration capabilities.

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, a related field, or equivalent experience.
10+ years of experience in data warehousing, data engineering, or analytics environments, including enterprise-scale platforms.
5+ years of leadership or management experience, including leading managers or team leads.
Proven ownership of an enterprise data strategy and roadmap, and delivery of large, cross-functional data initiatives.
Experience delivering data for AI and machine learning, exposing data through APIs and modern access methods, and partnering with data science or AI teams.
Strong expertise with SQL Server, Oracle, ETL/ELT development, and enterprise data modeling.
Experience with Azure, AWS, or Google Cloud data platforms and modern lakehouse architectures.
Experience supporting ERP ecosystems such as Oracle EBS, SAP, Workday, or Dynamics and integrating ERP data into analytics platforms.
Experience owning platform budgets and vendor or managed-service-provider relationships.
Experience establishing enterprise-scale data governance, quality, and security programs.
Strong functional understanding of Finance, Accounting, Procurement, and Supply Chain business processes.
Experience supporting enterprise ERP ecosystems, including Oracle EBS modules such as Financials, Procurement, Supply Chain, Inventory, Projects, and HR.
Experience with oil and gas operational, drilling, production, and financial data environments, upstream processes, and operational analytics.
Hands-on Microsoft Fabric experience across Lakehouse, Warehouse, Data Factory, Real-Time Analytics, OneLake, Power BI and ERP integration, self-service reporting, governance, security, workspace administration, and AI-enabled analytics.
Experience with enterprise data lake architecture, lakehouse and medallion architecture, Delta Lake and Delta Live Tables, Azure Data Lake Storage (ADLS), Azure Synapse Analytics, and Microsoft Fabric.
Experience with Databricks administration and optimization, Apache Spark and PySpark, real-time and streaming architectures, ETL modernization, and change data capture (CDC).
Experience with MCP servers, REST and data APIs, real-time data services, data products and semantic layers for AI and application consumption, and MLflow or AI/ML data enablement.
Knowledge of data governance and master data management, Databricks SQL and Unity Catalog, Fabric governance and administration, CI/CD and DataOps, and GitHub, Git, and Azure DevOps.
Experience with analytics and BI tools such as Power BI, Tableau, Cognos, and OBIEE, and languages including Python, SQL, and Spark.
Organizational leadership, including mentoring leaders and teams and setting talent and skills strategy.
Executive communication and stakeholder management skills, with the ability to influence across functions.
Strategic thinking combined with sufficient technical depth to make sound architecture decisions.
Financial acumen for platform cost and value, and disciplined prioritization across complex initiatives.

Nice To Haves

Advanced degree preferred.
Preferred industry experience in Oil and Gas, Manufacturing, Energy, Financial Services, Healthcare, Retail, or Supply Chain.

Responsibilities

Deliver a scalable, accessible data repository to power AI models, tools, and products.
Expose data to AI through Model Context Protocol (MCP) servers, APIs, and other access methods.
Establish data models as the source of truth in alignment with Digital Operations and Digital Drilling Solutions.
Define the type and age of data needed for modeling and ensure AI initiatives can access required data when needed.
Own and execute the enterprise data engineering strategy and multi-year roadmap aligned with business, functional, and IT priorities.
Lead and develop data engineering managers, leads, ETL and BI developers, and data architects across multiple locations; build organizational skills, bench strength, and succession.
Set architecture direction and standards for enterprise data lakes, lakehouses, warehouses, and cloud analytics platforms, and govern adoption.
Own data platform budget, capacity, and vendor and managed-service-provider relationships, partnering with Supply Chain on negotiations.
Establish and operate enterprise data governance, quality, security, and master data management programs.
Deliver trusted business intelligence, KPI dashboards, and self-service reporting on the enterprise data foundation.
Lead modernization and migration from legacy platforms to modern cloud ecosystems.
Integrate ERP data, including Oracle EBS and SAP, 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 value delivered.
Ensure platform reliability, performance, cost efficiency, and DataOps and CI/CD discipline.
Design enterprise reporting and analytics for operational and financial decision-making in partnership with relevant business leaders.

Benefits

Comprehensive medical, dental, vision, and life insurance
Flexible Spending or Health Savings Accounts
401k match
Paid Leave Plans
Parental and Adoption Benefits
Disability Coverage
Employee Assistance Program
Educational Assistance
Learning and Development Opportunities
Flex-scheduling available for qualifying positions to achieve work-life integration