Job Description

Job Description

Role: Sr. Data Modeler/Architect

Experience Level: 8–12+ years

Location: Tampa, FL, Dallas, TX, or Basking Ridge, NJ

Role Overview

We are seeking a Data 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) .

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