Telecom Network Data Performance Architect @ qode.world

Data & Analytics (1)

Role Overview

We 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 & Experience

Telecom 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).

Telecom Network Data Performance Architect

Data Modeling, Google Cloud Platform

qode.world

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