Senior Data Engineer, Network Intelligence

Xplore Inc•Oni, PE

About The Position

As a Senior Data Engineer on the Network Intelligence team, you will own the end-to-end data pipeline function that powers Xplore's network analytics, observability, and AI capabilities across Fiber, Fixed Wireless, and Satellite platforms in both cloud and on-prem environments. You will design and operate the Bronze-to-Silver-to-Gold medallion pipelines for all network telemetry domains, ensuring that on-premise network modeling outputs are reliably structured, governed, and delivered as trusted enterprise Gold-tier assets. This role spans both cloud and on-premises platforms, including building, maintaining, and optimizing data pipelines and supporting infrastructure on-prem—not just migrating workloads to the cloud. Your work directly underpins predictive analytics, ML model training, and operational dashboards consumed by network engineering, operations, and executive audiences. You will work in a cross-functional squad alongside the Network Intelligence & Automation Specialist, Data Scientists, and value-stream AI/Observability engineers, contributing to platform standards and mentoring intermediate engineers on the team.

Requirements

7+ years of experience in data engineering with production-grade pipeline development.
Expert-level Databricks experience: Spark optimization, Delta Lake, Unity Catalog, and Databricks Workflows or Delta Live Tables.
Strong Python and PySpark for production data engineering.
Solid understanding of medallion architecture (Bronze / Silver / Gold) and enterprise data governance principles.
Experience with streaming or near-real-time ingestion patterns: Kafka, Event Hubs, or Databricks Auto Loader.
Proficiency with Azure Data Lake Storage Gen2 and Azure-based data platform components.
Solid data modeling skills for time-series and high-frequency event datasets.
Strong communication skills and demonstrated mentorship experience

Nice To Haves

Familiarity with network telemetry data sources: SNMP, syslog, NetFlow, RAN KPIs, or equivalent.
Telecom, FWA, or infrastructure analytics domain experience.
Experience with On-Prem Kafka is a bonus.
Familiarity with Terraform or infrastructure-as-code for pipeline environment provisioning.
Databricks Certified Data Engineer (Associate or Professional).
Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.

Responsibilities

Design and build production-grade ELT pipelines in Databricks (PySpark, Delta Live Tables, Databricks Workflows) ingesting telemetry from RAN, transport, core, and cloud network platforms.
Own and maintain Bronze, Silver, and Gold tier datasets for all network domains, including schema governance, SLA adherence, and data quality standards in Unity Catalog.
Design, build, and maintain data pipelines and supporting components across both cloud and on-premises environments, including new on-prem solutions required for network telemetry and analytics workloads—not only cloud migration initiatives.
Deliver structured Bronze and Silver tier network modeling outputs into the Corporate Enterprise Gold tier, ensuring alignment with enterprise data architecture standards.
Apply partitioning, liquid clustering, and incremental load patterns to support large-scale time-series and event-driven network telemetry data.
Define and document canonical data models for network telemetry entities: cells, sites, circuits, alarms, and performance counters.
Instrument pipelines with data quality checks, alerting, and SLA monitoring to ensure operational reliability.
Partner with Data Scientists to produce feature-engineered Gold datasets suitable for ML model training and inference pipelines.
Collaborate with the GIS Data Engineer to integrate geospatial dimensions into network telemetry datasets.
Translate network engineering data requirements into structured pipeline specifications and delivery roadmaps.