About The Position

The Sr. Manager, Analytics and Operational Data Governance is a business-embedded leader within the Rig Technologies Operational Excellence function. Reporting to the Vice President, Process Excellence and Analytics, this role is responsible for advancing business performance through trusted data, standardized KPIs, and actionable analytics. The role leads the use of analytics to identify opportunities for revenue growth, margin improvement, cost reduction, and improved customer service, while establishing governance for critical operational data, reporting, and performance measures across the business unit. This is not an IT or Enterprise Systems role; it sits within the business and works closely with operations, supply chain, commercial, finance, and other functional leaders to improve visibility, alignment, and execution. The role also serves as a key business interface to the Corporate Enterprise Systems team to help prioritize and govern data, systems, and interface improvement initiatives, and leads a team of analysts responsible for delivering insights, performance reporting, and decision support to the business.

Requirements

  • Bachelor’s degree in Engineering, Analytics, Information Systems, Computer Science, Finance, or a related field required.
  • 10+ years of progressive experience in analytics, business performance, operational excellence, data governance, or related disciplines.
  • 5+ years of leadership experience in a business-facing role.
  • Demonstrated success building KPI frameworks, business reporting, and governance practices in a complex operating environment.
  • Strong understanding of operational processes, performance management, and cross-functional business execution.
  • Strong familiarity with ERP systems and experience using ERP data, process flows, and related reporting structures to support analytics, KPI governance, and operational improvement.
  • Knowledge of modern analytics, data, and reporting tools and technology stacks, including Power BI, Tableau, SQL, Snowflake, Databricks, Microsoft Fabric, Azure data services, Alteryx, Python, and related analytics or machine learning libraries.
  • Proven ability to exercise influence and drive alignment without direct authority.
  • Strong communication, facilitation, and stakeholder engagement skills.

Nice To Haves

  • Master’s or PhD degree in a relevant field is strongly preferred.
  • Experience in manufacturing, industrial, energy, or other operationally complex environments.
  • Experience supporting business transformation, process standardization, or continuous improvement initiatives.
  • Familiarity with ERP-based reporting, enterprise data structures, and cross-functional performance management processes.

Responsibilities

  • Lead analytics and operational data governance for the RT business unit within the OpEx function.
  • Drive analytics that support revenue growth, margin improvement, cost reduction, and enhanced customer service, including opportunities in pricing, service performance, inventory optimization, forecast accuracy, and operational efficiency.
  • Partner with business leaders to identify priorities and deliver actionable insights, dashboards, scorecards, and performance measures that support decision-making and business outcomes.
  • Establish and govern standardized KPIs, business definitions, reporting logic, and critical operational data to improve consistency, transparency, and decision quality.
  • Strengthen data ownership, stewardship, and data quality practices across key business processes and reporting domains.
  • Serve as the business interface to the Corporate Enterprise Systems team, helping prioritize, monitor, and govern data, systems, and interface improvement initiatives across ERP, reporting, planning, and operational platforms.
  • Lead and develop a team of analysts to deliver actionable insights, performance reporting, and analytics-driven decision support for the business.
  • Improve business visibility and reduce conflicting reporting through scalable, business-led analytics and governance practices.
  • Build cross-functional alignment and organizational capability to support execution, performance management, and continuous improvement.
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