Business Analyst – RMA Spend Cube

Posted:
4/13/2026, 1:07:29 AM

Experience Level(s):
Senior

Field(s):
Business & Strategy ⋅ Data & Analytics

Workplace Type:
Remote

As the global leader in high-speed connectivity, Ciena is committed to a people-first approach. Our teams enjoy a culture focused on prioritizing a flexible work environment that empowers individual growth, well-being, and belonging. We’re a technology company that leads with our humanity—driving our business priorities alongside meaningful social, community, and societal impact.

Job Overview: Ciena Corporation is seeking an experienced Business Analyst to join our Service Operations organization. This individual will serve as the lead developer and operator of the RMA Spend Cube, a single source of truth analytics platform enabling multi-dimensional spend visibility and cost reduction insights across suppliers, categories, and regions.

This role is responsible for designing, building, automating, and refining complex data pipelines and business logic that transform raw data into scalable, trusted insights. It requires someone who can independently architect and maintain data-driven solutions while deeply understanding the business context needed to support operational decision-making and enterprise-level analytics.

Key Responsibilities:

  • Lead development and ongoing operation of the RMA Spend Cube, ensuring it serves as a reliable, scalable, single source of truth for spend and analytics.
  • Build, automate, and optimize data pipelines that integrate and transform data from multiple sources into clean, structured datasets for analysis.
  • Design and implement complex business logic and transformation layers (e.g., multi-layer rules, calculations, and reconciliations) that enable automated reporting and insights.
  • Translate business needs into technical solutions by working closely with stakeholders to understand requirements and independently design appropriate data structures and logic.
  • Implement monitoring, validation, and error-checking mechanisms to ensure data accuracy, integrity, and consistency across pipelines and outputs.
  • Continuously enhance automation and tooling to improve efficiency, reduce manual effort, and scale analytics capabilities across the organization.
  • Support ad hoc and recurring analytics by enabling flexible, well-structured data access and reporting layers.
  • Ensure alignment between data pipelines, business rules, and evolving operational processes.

Required Skills & Experience:

  • Experience with ETL, data integration, and data transformation processes, including familiarity with tools like Pentaho Data Integration (a plus).
  • Ability to analyze and interpret complex datasets, automate data processes, and assess business relevance.
  • Proficiency in scripting and programming for data analysis and logic implementation (e.g., SQL); advanced Excel capabilities.
  • Strong problem-solving skills with the ability to think critically about data connections, structure, and business context.
  • Effective communication skills, both technical and business-oriented, ensuring alignment between business goals and data solutions.

Preferred Qualifications:

  • Experience with Pentaho Data Integration, Snowflake, Oracle, MySQL, VBA, and other scripting languages.
  • Experience building or maintaining centralized data products, analytics platforms, or “single source of truth” systems.
  • Exposure to automation of business processes through data-driven logic and workflows.
  • Familiarity with data visualization tools (e.g., Power BI, ThoughtSpot).


At Ciena, we are committed to building and fostering an environment in which our employees feel respected, valued, and heard.  Ciena values the diversity of its workforce and respects its employees as individuals. We do not tolerate any form of discrimination.

Ciena is an Equal Opportunity Employer, including disability and protected veteran status.

If contacted in relation to a job opportunity, please advise Ciena of any accommodation measures you may require.