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# Manager, Data Operations

- **Company:** Harley-Davidson, Inc.
- **Location:** Milwaukee, WI, United States
- **Experience:** Expert
- **Salary:** $119,000 - $178,100
- **Contract:** Permanent contract
- **Skills:** Microsoft Azure, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Systems, Machine Learning, Meta-Data Management, DataOps, System Availability, Data Strategy, Microsoft Fabric, Information Technology, Performance Monitor, Data Management
- **Published:** October 26, 2026
- **Apply:** https://diversityjobs.com/career/18731560/Manager-Data-Operations-Wisconsin-Milwaukee

## About the Role

Bachelor's Degree Required
Education Specifications

Bachelor's degree in Engineering, Computer Science, or a related technical discipline.
Experience Requirements

This position typically requires a minimun of 8+ years of experience in data operations, data governance, or data engineering, with at least 5 years in a management role. In addition, the successful candidate will have demonstrated the following:

 * Technical Skills: Strong expertise in data infrastructure, data governance, ETL/ELT processes, and database management. Familiarity with Microsoft Fabric is desired.
 * Data Governance Leadership: Extensive experience in development and oversight of Data Governance practices across the entire organization, with a track record of building a highly functional Data Governance Council.
 * Leadership: Demonstrated ability to lead, mentor, and develop a high-performing team, and to foster a culture of continuous improvement.
 * Communication: Strong communication skills, with the ability to work effectively across technical and non-technical stakeholders., Applicants must be currently authorized to work in the United States.

## Description

We are seeking a highly skilled Manager, Data Operations to lead and manage our data operations team. In this critical role, you will ensure our data systems are efficient, reliable, and secure. You will oversee the design, development, and management of the organization's data platform infrastructure, along with the development and enforcement of data governance strategies and policies to ensure data accuracy, security, and appropriate usage., * Data Operations Management: Manage the day-to-day activities of the data operations team, ensuring data availability, reliability, and security to support data integration, storage, processing, and analytics.

 * Data Platform Infrastructure: Oversee the architecture, development, and maintenance of the data platform infrastructure, ensuring high availability, performance, and scalability.
 * Data Governance: Develop, implement, and enforce data governance frameworks, policies, and standards, including data cataloging, lineage, quality, and stewardship processes.
 * Stakeholder Collaboration: Partner with analysts, data governance leads, and business stakeholders to align data platform capabilities with organizational goals and to support reporting, analytics, and machine learning initiatives.
 * Leadership in Data Governance Council: Act as a key leader within the data governance council to ensure cross-functional alignment and effective data stewardship across the organization.
 * Team Leadership & Development: Lead, mentor, and develop a team of data operations professionals, fostering a culture of excellence, collaboration, and continuous improvement.
 * Training & Development: Provide training and support to team members to enhance their skills and ensure high performance.
 * Project Management: Oversee data platform-related projects, ensuring timely delivery within scope and budget, while managing risk and addressing any issues.
 * Performance Reporting: Generate and present regular reports on data platform performance, issues, and improvements to senior management.
 * Tool Evaluation & Implementation: Evaluate, select, and implement data tools and platforms that align with the organization's data strategy.
 * Microsoft Azure: Apply knowledge of Microsoft Azure including Fabric to enhance the data platform infrastructure and optimize data processes where applicable.