Sr. Manager, Data Engineering

Posted 4 Hours Ago
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Tulsa, OK, USA
In-Office
Senior level
Energy
The Role
Own the enterprise data engineering strategy, roadmap, architecture, governance, and platform investment. Lead multi-location data engineering teams and managers while delivering scalable lakehouse, warehouse, BI, and AI data capabilities. Oversee modernization, ERP integrations, data quality, security, master data management, DataOps, and cloud platform operations. Partner with executive stakeholders across Finance, Operations, Supply Chain, and IT to prioritize initiatives, manage vendors and budgets, and deliver reliable, cost-effective analytics platforms.
Summary Generated by Built In

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

#LI-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 upstream business processes and operational analytics.
  • Track record designing enterprise reporting and analytics for operational and financial decision-making, partnering with Operations, Supply Chain, Finance, and executive leadership.
  • Hands-on Microsoft Fabric experience: unified analytics across Fabric Lakehouse, Warehouse, Data Factory, and Real-Time Analytics; OneLake and enterprise data consolidation; integration with Azure Data Lake, Power BI, and ERP systems; self-service reporting; Fabric governance, security, and workspace administration; and AI-enabled analytics.

Modern Data Platform and Technical Skills

  • Data platform and architecture: enterprise data lake architecture, lakehouse design and medallion architecture, Delta Lake and Delta Live Tables, Azure Data Lake Storage (ADLS), Azure Synapse Analytics, and Microsoft Fabric (Lakehouse, Warehouse, Data Factory, Real-Time Analytics, and OneLake).
  • Processing and pipelines: Databricks platform administration and optimization, Apache Spark and PySpark, real-time and streaming data architectures, ETL modernization, and change data capture (CDC).
  • AI data enablement and access: Model Context Protocol (MCP) servers, REST and data APIs, real-time data services, and data products and semantic layers for AI and application consumption; MLflow and AI/ML data enablement.
  • Governance and DataOps: data governance and master data management, Databricks SQL and Unity Catalog, Fabric data governance, security, and workspace administration, CI/CD pipelines and DataOps, and GitHub, Git, and Azure DevOps.
  • Analytics and BI: Power BI, Tableau, Cognos, and OBIEE.
  • Languages: Python, SQL, and Spark.

 

What you need: 

Required Qualifications

  • Bachelor's degree in Computer Science, Information Systems, Engineering, a related field, or equivalent experience; advanced degree preferred.
  • 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, not only individual contributors.
  • 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, including 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 data governance, quality, and security programs at enterprise scale.

Soft Skills

  • Organizational leadership: leading and mentoring leaders and teams, and setting talent and skills strategy.
  • Executive communication and stakeholder management, with the ability to influence across functions.
  • Strategic thinking paired with enough hands-on technical depth to make sound architectural decisions.
  • Financial acumen for platform cost and value, and disciplined prioritization across multiple complex initiatives.

Preferred Industry Experience

  • Oil and Gas, Manufacturing, Energy, Financial Services, Healthcare, and Retail and Supply Chain.

What we offer: 


At H&P, our commitment to our people is at the forefront, and that includes benefits that provide employees a sense of health and financial security. We know that life continues outside of employment and actively caring of our people is our priority. 

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

The job level and associated compensation for this position will be determined based on the candidate’s experience, qualifications, and alignment with the role’s requirements. Final compensation for this role may vary depending on individual factors. 


H&P is committed to employing a diverse workforce. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, or disability. 

Thank you for your interest in joining our team!

Skills Required

  • Bachelor's degree in Computer Science, Information Systems, Engineering, a related field, or equivalent experience
  • Advanced degree
  • 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
  • Experience owning an enterprise data strategy and roadmap and delivering large cross-functional data initiatives
  • Experience delivering data for artificial intelligence and machine learning, including APIs and modern access methods
  • Strong expertise with SQL Server, Oracle, ETL or 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 organizational leadership, executive communication, stakeholder management, strategic thinking, technical architecture judgment, and financial acumen
  • Experience in oil and gas, manufacturing, energy, financial services, healthcare, retail, or supply chain
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The Company
HQ: Tulsa, OK
4,030 Employees
Year Founded: 1920

What We Do

Since 1920, H&P has been the industry’s most trusted partner in U.S. land, international and offshore drilling productivity and reliability. Using cutting edge rig technologies and drilling solutions; we’re building upon a century of success while continuing to improve reliability, safety and efficiency for our customers.

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