Engineer III - Network Planning

Verizon•Irving, TX

21d•Hybrid

About The Position

We are seeking an innovative and technically advanced Engineer III to spearhead our data engineering, advanced analytics, and network-based detection initiatives aimed at combating illegal robocalling, SIMBOX fraud, and emerging wireless network threats. In this role, you will take ownership of end-to-end analytics, transforming complex network telemetry and high-volume carrier logs into proactive trend forecasting and strategic insights. You will collaborate closely with a diverse cross-functional ecosystem—including CISO, Network Systems, Fraud, Security, Risk Management, and Voice Identity teams—to design, automate, and harden our network defenses against sophisticated malicious activity. A central focus of this position is the aggressive adoption and integration of Generative AI tools (such as Gemini and Claude) and knowledge management platforms (like NotebookLM) to streamline daily workflows, architect complex data pipelines, and continuously optimize runtime efficiencies.

Requirements

Bachelor's degree or four or more years of work experience.
Three or more years of relevant experience required, demonstrated through work experience and/or military experience.
Programming experience in Python, specifically leveraging Pandas for data vectorization, text processing, JSON conversion, and building defensive data guardrails.
Experience using Generative AI workflows (e.g., Gemini, Claude) to refactor, debug, and optimize execution runtimes for legacy scripts.

Nice To Haves

Experience in network security, data engineering, or telecommunications analytics.
Advanced proficiency in constructing multi-layered BigQuery SQL queries (utilizing CTEs, indexing optimization, and handling tri-value null parameters).
Foundational comprehension of cellular and IP messaging components, including UE identification structures, SIP signaling protocols, and Netscout register telemetry.
Proven track record of compiling and presenting complex analytical conclusions and data dashboards into clear executive-level communications.
Hands-on knowledge of voice security authentication frameworks, specifically STIR/SHAKEN signing/verification structures and fraud-mitigation analytics.
Demonstrated ability to build automated data pipelines that transition unstructured text/JSON logs into centralized analytics indices like Kibana or Elasticsearch.
Prior experience managing multi-department data recovery initiatives across complex corporate cross-functional environments.

Responsibilities

Leveraging advanced AI platforms (e.g., Gemini, Claude) to engineer robust data solutions, resolving intricate logical conflicts, and establish defensive data guardrails within processing pipelines.
Utilizing NotebookLM to ingest and analyze critical technical documentation (HLDs, LLDs, call flows, configurations, capacity limits) to scale awareness, document custom workflows, and maintain project sustainability across teams.
Developing, testing, and optimizing advanced BigQuery SQL scripts using Common Table Expressions (CTEs), inline Python Pandas code, and custom macros and decoders to isolate high-confidence spoofing indicators across Netscout NG1 and nBA platforms.
Executing, maintaining, and developing visualization tools and automated query pipelines to isolate temporary markers of local network abuse.
Transitioning heavy data delivery mechanisms to high-performance, secure cloud storage architecture, implementing automated query deduplication and indexing to prioritize processing speed ahead of string-matching calculations.
Owning the technical lifecycle and data ingestion of security telemetry into analytics visualization dashboards, including Kibana (NG1/nBA feeds), Tableau (FDV spam overlays), and Ribbon Analytics platforms for traffic pumping monitoring.
Formulating, establishing, and tracking sophisticated KPIs regarding network blocking progress, STIR/SHAKEN metrics, and fraud mitigation effectiveness to deliver high-resolution strategic updates to executive leadership.
Driving analytical strategies to combat Enterprise and Verizon Brand Impersonation by correlating complex datasets, evaluating STIR/SHAKEN trends, and supporting consumer-facing filter utilities (Call Filter, Spam Alerts).
Partnering with Finance, Carrier Management, and Fraud teams to analyze monthly traffic anomalies, using automated scripts and platform insights to systematically reduce telco access costs and operational financial losses.
Efficiently packaging automated industry tracebacks (e.g., ITG, YouMail), execute ETNI processes, and collaborate with Legal and external authorities to fulfill subpoena and external investigation needs.