Sr Manager, Data & Advance Analytics

Since 1892, OPW customers have been able to count on us to revolutionize fluid-handling operations around the world. As a global leader in fluid-handling solutions, the mission of OPW is to be a developer of a comprehensive array of innovative fluid-handling solutions that our customers can consistently and reliably count on. These include loading and unloading systems for high-value hazardous and non-hazardous bulk products; railcar and transport tank-truck valves, gauging devices and tank-monitoring systems; automated storage-terminal controls and systems; and regulators, fittings, valves, vaporizers, vacuum-jacketed piping and gas-handling systems for the safe handling and distribution of cryogenics and industrial gases. OPW has more than 2,000 employees with manufacturing operations in North America, Europe and China, and sales offices around the world. 

 

OPW is part of the Clean Energy & Fueling segment of Dover (NYSE: DOV).

 

Position Summary
The Senior Manager, Data & Advanced Analytics, will lead the transformation of OPW’s business intelligence capabilities into a modern enterprise analytics platform that enables data-driven decision making across the organization. Reporting to the Sr. Director, Digital & IT, this role will be responsible for designing and implementing a centralized OPW Data Lake that integrates data across multiple ERP platforms and key enterprise systems, while establishing a structured data governance framework in partnership with the Dover Data Governance Center of Excellence (COE). By creating a scalable cloud-based analytics foundation using Microsoft Fabric, Azure, and Power BI, this role will modernize OPW’s reporting environment, enabling self-service analytics, improved data transparency, and advanced analytical capabilities across the enterprise.

 

Following the successful implementation of the data lake and governance framework, this role will also serve as OPW’s internal data science leader, applying advanced analytics and AI technologies to deliver deeper insights across key business domains including sales performance, inventory optimization, and margin analysis. This position will play a critical role in helping OPW transition from traditional reporting to advanced analytics and AI-enabled decision support.
 
 
Core Responsibilities

Enterprise Data Architecture & Data Lake Development
•    Lead the design and implementation of the OPW enterprise data lake, integrating data from multiple ERP systems and key enterprise platforms.
•    Develop scalable data pipelines and data models leveraging Azure, Microsoft Fabric, and Power BI.
•    Integrate data from ERP systems, Salesforce, OneStream, eCommerce platforms, and other enterprise systems into a unified analytics environment.
•    Partner with the Dover Data Governance COE to ensure alignment with enterprise data standards, architecture principles, and security frameworks.
•    Establish scalable data architecture that supports both operational reporting and advanced analytics use cases.
•    Work with internal IT teams and external partners to build a robust, high-performance analytics platform capable of supporting global operations.
 
 

Data Governance & Data Quality
•    Establish and operationalize data governance practices across OPW, aligned with Dover enterprise standards.
•    Define and implement data ownership, stewardship, and accountability across key business domains.
•    Lead initiatives to improve data quality, data standardization, and master data consistency across ERP systems.
•    Implement governance frameworks that ensure data integrity, compliance, and sustainable analytics development.
•    Partner with business leaders to establish clear data stewardship roles across operational functions.
 
 

Business Intelligence Transformation
•    Transform OPW’s existing BI reporting environment into a modern self-service analytics platform.
•    Lead the development of enterprise dashboards and analytics solutions using Power BI.
•    Establish standardized reporting models and semantic layers that support scalable analytics across the organization.
•    Enable business users to independently access and analyze data through self-service analytics capabilities.
•    Ensure BI solutions provide actionable insights that improve operational performance and decision speed.
 
 

Advanced Analytics, Data Science & AI
•    Develop predictive and prescriptive analytics models to support business priorities such as:
o    Inventory optimization
o    Demand forecasting
o    Sales performance analysis
o    Margin improvement
•    Apply advanced analytics techniques, including machine learning and AI, to uncover actionable insights across OPW’s data eco