via indeed · 1 June 2026 ·5 days ago

Blue Planet Data Management Lead

Ciena
London Full-time
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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.

Ciena is advancing intelligent, automated networks through its Blue Planet portfolio by enabling data\-driven innovation and AI\-powered operations. This role leads the definition of data strategy, architecture, and productization for telecom data, enabling scalable digital twin capabilities and data platforms that support next\-generation network operations. The position plays a critical role in aligning data foundations with AI, automation, and product innovation across the portfolio.

How you will make an impact:

  • Define and own the canonical telco data model and ontology across network topology, service lifecycle, inventory, assurance, and OSS domains

  • Align data models with industry standards including TM Forum Open APIs, SID/eTOM, Open Digital Architecture, YANG/NETCONF, and TOSCA

  • Drive adoption of ontology models across product teams as the semantic foundation for data exchange, AI training, and digital twin deployment

  • Develop and lead the data fabric product architecture, including federated access, streaming pipelines, virtualization, metadata management, and lineage tracking

  • Translate data architecture vision into scalable, cloud\-native and microservices\-based implementations in collaboration with engineering teams

  • Define and deliver the telco digital twin strategy, including use cases such as network optimization, predictive maintenance, and simulation

  • Engage with customers, partners, and industry forums to validate solutions, influence standards, and position the portfolio in the market
The must haves:
  • Education: Bachelor’s degree in Engineering or Software Engineering with telecommunications, networking, or communications systems concentration, or equivalent experience

  • Experience: 15\+ years of experience in the telecom software industry with at least 5\+ years of product line management experience

  • Application of telecom data modeling, schema design, graph or ontology structures, and enterprise data management tools

  • Application of AI and ML data requirements including feature stores, training data pipelines, data lineage, and model grounding techniques for GenAI or LLM use cases

  • Background in OSS environments including network automation, orchestration, inventory, assurance, and network management systems

  • Exposure to telecom network domains including fixed, mobile or RAN, and cable or MSO across core, transport, and access layers

  • Experience introducing complex technical products or architectures into Tier\-1 CSP or network provider environments
Nice to haves:
  • Background in cloud\-native architectures including Kubernetes, microservices, and cloud data platforms

  • Exposure to multi\-cloud environments

  • Collaboration across engineering, product management, marketing, and field organizations

  • Engagement with industry analysts and participation in analyst briefings

  • Contribution to industry forums such as TM Forum, MEF, ETSI, or ONF

  • Development of technical content including whitepapers, blogs, or conference presentations

  • Support of go\-to\-market strategy and product positioning
\#LI\-ST1

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.

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