Xplore Inc. is Canada’s fibre, 5G and satellite broadband company for rural living. Xplore is 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 innovative broadband services for better every day rural living, for today and future generations.
Role Overview
As an Analytics Engineer for Network Intelligence on Data & AI team, you will bridge the gap between Xplore's raw network and operational data and the dashboards, KPIs, and self-serve analytics that engineering, operations, and leadership teams rely on daily.
You will own the semantic layer, curated Gold-tier analytical datasets across both on-prem and cloud data platforms, and Databricks AI/BI dashboards that surface real-time and historical network intelligence across Fiber, Fixed Wireless, and Satellite domains. This role is not limited to cloud migration work: it also requires designing, building, and operating analytical datasets, transformations, and reporting assets directly on-prem where business and operational needs require it. Unlike a pure data engineer who focuses on pipeline infrastructure, or a data scientist focused on modeling, your specialty is making data reliable, understood, and usable by the widest possible audience: you own metric definitions, dashboard governance, and the translation of operational data needs into clean, documented analytical assets.
Key responsibilities include:
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Define, document, and maintain canonical KPI and metric definitions for network health, incident volume, capacity utilization, and customer experience indicators in Unity Catalog.
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Build and own the semantic layer (Databricks AI/BI datasets) underpinning self-serve analytics for network operations, engineering, and leadership stakeholders.
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Design and build operational and executive dashboards in Databricks AI/BI covering real-time network health, incident trends, performance benchmarks, and customer impact metrics.
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Develop automated alerting and correlation views that reduce noise for network operations teams and accelerate root cause identification.
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Build curated Gold-tier analytical tables and transformation layers across both on-prem and cloud platforms using SQL and PySpark, applying business logic, aggregations, and dimensional modeling patterns.
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Implement data quality checks and automated validation to ensure analytical outputs are accurate before reaching business consumers.
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Partner with Data Engineers to surface upstream data quality issues and define requirements for Silver-to-Gold transformations.
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Act as the subject matter expert for network and operations data consumers, supporting self-serve analytics adoption across engineering and ops teams.
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Produce clear data dictionaries, lineage documentation, and onboarding guides for all owned analytical assets.
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Support executive-level reporting with accurate, clearly structured KPI outputs tied to network quality and customer experience.
The ideal candidate will possess:
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5+ years of analytics engineering, BI development, or data analysis experience in a data-intensive environment.
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Expert SQL skills: complex analytical queries, window functions, dimensional modeling, and metric grain definitions at scale.
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Hands-on Databricks experience: SQL Warehouses, AI/BI Dashboards, and Unity Catalog; or equivalent modern data stack experience (Snowflake, BigQuery+ Looker or dbt).
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Strong understanding of data modeling concepts: star schema, slowly changing dimensions, and single-source-of-truth metric governance.
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Demonstrated ability to translate ambiguous business questions into well-defined analytical datasets and dashboard specifications.
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Proficiency in Python for lightweight transformations and pipeline scripting.
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Excellent written and verbal communication skills; comfort presenting analytical findings to Director and VP-level audiences.
Preferred Qualifications:
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Experience building and supporting analytics or transformation layers on-prem as well as in Databricks/cloud environments; not limited to migration initiatives.
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Background in network operations, telecommunications, or infrastructure analytics.
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Familiarity with Grafana, Datadog, or Prometheus as complementary network observability tools.
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Experience designing role-based access controls and data governance frameworks in a cloud or on-prem data platform.
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Bachelor's degree in Computer Science, Information Systems, Mathematics, or a related field.
Condition of Employment:
As a condition of employment and in order to comply with industry related data security standards, this position is subject to the successful completion of a Criminal Background Check. Details will be supplied to applicants as they move through the selection process.
Xplore is committed to creating an accessible environment and will accommodate disabilities during the selection process. Please let your recruiter know during the selection process of any accommodation needs.
