Data Management Analyst

Moog Inc.•Torrance, CA

3d•$105,000 - $140,000•Onsite

About The Position

Moog’s Military Aircraft Group is seeking an experienced individual contributor to advance data governance, organizational change management, and data fluency across the MAG Business Modernization Program. Working independently with limited supervision and in partnership with the Data Management Business Partner and functional stakeholders, the analyst defines data needs, analyzes and visualizes data, encourages adoption of governance practices, and turns business questions into actionable insights. Depending on the assignment, the analyst may lead defined components of data management and analytics projects, processes, or programs. This is a first-shift, onsite position at either the East Aurora, New York, or Torrance, California location. Travel is less than 10%. The position requires access to U.S. export-controlled information.

Requirements

Bachelor’s degree in data analytics, business analytics, computer science, or a related discipline.
At least 5 years of relevant experience in data analytics, business intelligence, data management, data governance, or a related field.
Advanced knowledge of data analytics concepts, methods, and principles, including requirements definition, data preparation, analysis, modeling, visualization, and interpretation.
Ability to connect analytics concepts and data management practices with business processes, stakeholder needs, and decision-making priorities.
Experience working independently on defined components or entire projects, processes, or programs, with minimal guidance and review at critical points.
Strong communication skills, including the ability to engage stakeholders within and outside the function and explain data concepts to technical and non-technical audiences.
Demonstrated ability to solve complex data or process problems using advanced data management and analytics knowledge and adapt established methods or solutions to new business contexts.

Nice To Haves

Experience supporting ERP, MES, or enterprise platform modernization programs.
Familiarity with structured delivery methods such as waterfall-hybrid, agile-hybrid, or stage-gate.
Experience with data, analytics, and reporting platforms such as Databricks, SQL Server, Power BI, Power Apps, or similar tools.
Experience in manufacturing, aerospace, or other operationally complex environments.

Responsibilities

Partner with the Data Management Business Partner to deploy data governance practices, organizational change management activities, and data fluency initiatives across the business.
Define and document business data requirements, data quality needs, and reporting and analytics use cases with functional stakeholders.
Collect, prepare, clean, analyze, and visualize data to identify patterns, trends, risks, and opportunities that support business decisions.
Develop dashboards, reports, and analytical outputs that convey insights and actionable recommendations to business users.
Help business teams understand and apply data standards, data ownership and stewardship responsibilities, and process expectations.
Contribute to organizational change management and communication activities that increase awareness and adoption of data management practices.
Communicate insights, recommendations, and data governance expectations to technical and non-technical stakeholders.
Identify opportunities to improve the efficiency, consistency, and automation of recurring data analysis, reporting, and data management processes.
As assigned, lead defined components of data governance, organizational change management, and data fluency initiatives with the Data Management Business Partner and business stakeholders.
Independently develop analytical models and advanced visualizations to address complex business questions and improve decision-making.
Solve complex data or process problems by applying advanced data management and analytics knowledge and adapting established methods to new business contexts.
Provide analytical input to data science, data mining, process improvement, or transformation initiatives as needed.
Coordinate, coach, guide, or review contributors’ work on assigned projects, processes, or programs while retaining independent responsibility for assigned deliverables.
Implement scalable improvements to recurring data analysis, reporting, and data management processes.