Data Engineer

About The Company

Xplore Inc. is Canada's fibre, 5G and satellite broadband company dedicated to transforming rural living through innovative connectivity solutions. Committed to the relentless pursuit of an improved broadband experience for all Canadians, Xplore is building a world-class fibre optic and 5G wireless network to enable cutting-edge broadband services. Our mission is to enhance everyday life in rural communities by providing reliable, high-speed internet access today and for future generations. We believe in bridging the digital divide and empowering rural populations with the same connectivity opportunities as urban centers, fostering economic growth, education, and social inclusion.

About The Role

As a Senior Data Engineer within the Network Intelligence team at Xplore Inc., you will play a pivotal role in managing and optimizing our data pipelines that support network analytics, observability, and artificial intelligence applications across our diverse platforms, including Fiber, Fixed Wireless, and Satellite. Your primary responsibility will be to design, develop, and maintain end-to-end data pipelines that facilitate the collection, processing, and governance of network telemetry data. You will ensure that data outputs are reliable, structured, and adhere to enterprise standards, supporting advanced analytics, machine learning models, and operational dashboards used by network engineers, operations teams, and executive leadership.

This role involves working across both cloud and on-premises environments, building scalable data pipelines, and supporting infrastructure to ensure data quality and availability. You will collaborate closely with cross-functional teams, including Data Scientists, Network Engineers, and AI/Observability engineers, to develop platform standards, mentor junior team members, and contribute to the continuous improvement of our data architecture. Your expertise will directly influence predictive analytics, network performance monitoring, and strategic decision-making processes.

Qualifications

The ideal candidate will possess over 7 years of experience in data engineering, with a proven track record of developing production-grade data pipelines. You should have expert-level proficiency in Databricks, including Spark optimization, Delta Lake, Unity Catalog, and Databricks Workflows or Delta Live Tables. Strong programming skills in Python and PySpark are essential for building reliable data processing solutions. A thorough understanding of medallion architecture (Bronze, Silver, Gold) and enterprise data governance principles is required, along with experience in designing and implementing streaming or near-real-time ingestion patterns using tools like Kafka, Event Hubs, or Databricks Auto Loader.

Proficiency with Azure Data Lake Storage Gen2 and other Azure-based data platform components is highly desirable. You should also have solid data modeling skills, especially for time-series and high-frequency event datasets. Excellent communication skills and prior experience mentoring team members are necessary to thrive in this collaborative environment.

Responsibilities

• Design and develop production-grade Extract, Load, Transform (ELT) pipelines utilizing Databricks, PySpark, Delta Live Tables, and Databricks Workflows to ingest telemetry data from various network components such as RAN, transport, core, and cloud platforms.
• Manage and maintain Bronze, Silver, and Gold tier datasets for all network domains, ensuring schema governance, data quality, and adherence to Service Level Agreements (SLAs) within Unity Catalog.
• Build and support data pipelines and infrastructure across both cloud and on-premises environments, including developing new on-prem solutions for network telemetry and analytics workloads, not limited to cloud migration efforts.
• Deliver structured network modeling outputs into the enterprise Gold tier, aligning with organizational data architecture standards and ensuring data consistency.
• Implement partitioning, clustering, and incremental load strategies to efficiently handle large-scale time-series and event-driven network telemetry data.
• Define and document canonical data models for network entities such as cells, sites, circuits, alarms, and performance counters.
• Instrument pipelines with comprehensive data quality checks, alerting mechanisms, and SLA monitoring to ensure operational reliability and data integrity.
• Collaborate with Data Scientists to produce feature-engineered datasets suitable for machine learning model training and inference pipelines.
• Work closely with GIS Data Engineers to incorporate geospatial data dimensions into network telemetry datasets, enhancing spatial analysis capabilities.
• Translate network engineering data requirements into detailed pipeline specifications and development roadmaps, ensuring timely delivery and high-quality outputs.

Benefits

Xplore Inc. offers a comprehensive benefits package designed to support the health, well-being, and professional growth of our employees. We provide competitive salary packages, health and dental insurance, and retirement savings plans. Employees have access to ongoing training and development programs to enhance their skills and advance their careers. We promote a flexible work environment that encourages work-life balance, including options for remote work where applicable. Additionally, employees benefit from a collaborative and inclusive workplace culture that values innovation, diversity, and continuous improvement. We also support various wellness initiatives and employee engagement activities to foster a positive work environment.

Equal Opportunity

Xplore Inc. is committed to fostering an inclusive and diverse workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, age, disability, or any other protected status under applicable laws. We believe that a diverse workforce enhances our ability to serve our customers and community effectively and are dedicated to creating an environment where everyone feels valued and empowered to contribute their best.