Job Description
Job DescriptionRole OverviewWe are seeking a Telecom Network Data Performance Architect with deep expertise in data modeling and architecture on Google Cloud Platform (GCP). The role focuses on building robust, scalable, and domain-driven data models for telecom network performance management, enabling analytics, AI/ML, and automation use cases across network operations and customer experience.Key Responsibilities· Design and implement logical, physical, and semantic data models for telecom network performance datasets (PM counters, CDRs, alarms, logs, probe data, OSS KPIs).· Develop time-series, geospatial, and hierarchical data models optimized for BigQuery and Dataflow pipelines.· Standardize telecom KPIs, KQIs, and service quality metrics into reusable data schemas for assurance and optimization.· Build and maintain enterprise data models aligned with TM Forum SID / industry standards.· Collaborate with data engineers to translate models into efficient ingestion, transformation, and storage patterns on GCP.· Ensure data normalization vs denormalization trade-offs, partitioning and clustering strategies, and performance tuning in BigQuery.· Define semantic layers for BI and analytics (Looker/Looker Studio) to expose network KPIs consistently.· Implement metadata, lineage, and cataloging using Dataplex for governed access to telecom datasets.· Guide data scientists and AI/ML engineers in feature store design and model-ready data sets.Required Skills & ExperienceTelecom Domain Modeling:· Strong understanding of network performance management data (RAN, Core, Transport, IP).· Experience in modeling KPIs, QoS/QoE metrics, SON, alarms, and service assurance data.· Familiarity with time-series, geospatial, and hierarchical relationships in network data.Data Modeling & Architecture (GCP):· Expertise in conceptual, logical, and physical data modeling for large-scale datasets.· Advanced knowledge of BigQuery partitioning, clustering, and optimization.· Hands-on with ER modeling tools (e.g., ERWin, Lucidchart, SQLDBM).· Experience with semantic modeling for BI platforms (Looker, Tableau, etc.).· Proficiency in SQL (BigQuery dialect) and Python for data validation.Cloud & Data Engineering Knowledge:· Exposure to Dataflow/Apache Beam for schema enforcement in pipelines.· Knowledge of Dataplex, Pub/Sub, Cloud Storage for modeling ingestion pipelines.· Experience in feature engineering & ML data model preparation (Vertex AI integration is a plus).
Preferred Qualifications· 8+ years in data architecture / modeling, with at least 3+ in telecom data.· Strong background in OSS/BSS data models and TM Forum SID frameworks.· Certification: Google Cloud Professional Data Engineer / Architect.· Exposure to 5G network data modeling (slicing, edge, IoT analytics).