Senior Intelligence Analytics Engineer
Xplore Inc.
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.
Senior Intelligence Analytics Engineer — Hands-on Technical LeadAs a hands-on technical lead in the Customer Intelligence & Analytics Centre of Excellence (COE), you will own the Customer Office’s gold-layer analytics foundation, validate pipeline design and data quality, automate manual processes, and enable generative AI (GenAI) and agentic AI use cases. You will combine reliable engineering with customer insights, analytics applications, and executive storytelling to build a scalable, AI-ready foundation and support business decisions.
Key responsibilities include:
Own Databricks gold-layer design, including curated and certified datasets, reusable transformation logic, and consistent key performance indicator (KPI) definitions. Partner with Data Engineering to validate pipeline design and end-to-end processing for correctness, scalability, and maintainability.
Analyze customer interaction transcripts, technical and repeat calls, Voice of Customer (VOC) data, customer journeys, and operational KPIs to identify root causes and recommend improvements across customer experience, contact centres, and field operations.
Build Databricks Apps, self-service analytics applications, and executive dashboards with clear user experience and visual storytelling.
Own analytics products from concept through adoption, including requirements gathering, design, development, testing, deployment, and continuous improvement.
Automate report delivery, data preparation, operational analytics workflows, and interactive presentation creation to reduce manual effort and communicate findings, business impacts, and recommendations.
Leverage Copilot, Claude, Genie, and AI technologies to improve productivity and accelerate insights.
Develop GenAI and agentic AI solutions, including intelligent agents, conversational analytics, and decision-support tools, using trusted, governed datasets and validated pipelines.
Establish automated pipeline and data validation, including source-to-target reconciliation and checks for accuracy, completeness, consistency, and freshness. Maintain monitoring to detect reliability issues, investigate failures, and coordinate corrective action.
Provide hands-on technical leadership through design reviews, engineering standards, documentation, and team guidance to support reliable production solutions.
Required Qualifications
At least 7 years of relevant experience in data, analytics, business intelligence, customer intelligence, or related fields, delivering production analytics solutions.
Experience building one or more of the following: AI agents, retrieval-augmented generation (RAG) solutions, conversational analytics solutions, or agentic workflows.
Experience with Databricks, Databricks SQL, and lakehouse architecture.
Demonstrated experience designing and building production-ready analytics applications or self-service analytics products, including Databricks Apps or comparable solutions.
Demonstrated hands‑on experience designing gold‑layer datasets and validating data pipelines, transformation logic, and source-to-target data accuracy, with automated testing, data quality controls, and reliability monitoring.
Experience automating data and analytics workflows and providing hands‑on technical leadership.
Strong SQL and analytical problem‑solving skills, including experience working with large, complex datasets.
Hands‑on Python experience for automation, pipeline and data validation, and GenAI or agentic AI development.
Strong communication and visual storytelling skills, demonstrated through executive dashboards and PowerPoint presentations.
Hands‑on use of Microsoft Copilot, Claude, Databricks Genie, ChatGPT, or comparable tools, with strong prompt engineering skills for analysis, insight generation, content creation, and business recommendations.
Ability to independently lead analytical projects from problem definition through recommendations and presentation.
Experienced in CI/CD, DevOps and automation practices.
Preferred Qualifications
Experience in telecom, contact centres, customer experience, customer care, workforce management, or customer intelligence, particularly with telecom call centre data is an asset.
Experience scaling adoption and continuous improvement of analytics products and AI solutions across business teams.
Experience analyzing transcripts, unstructured text, VOC, sentiment, or conversational intelligence data, and using customer journey analysis to identify friction and connect customer behaviours to operational and business outcomes.
Experience defining KPI frameworks, semantic data models, metric governance, and reusable business logic to support self‑service analytics.
Advanced implementation experience with vector search, RAG architectures, production agentic workflows, and AI assistants, supported by AI governance, large language model (LLM) evaluation and monitoring, and repeatable prompt refinement.
Databricks certifications in data analytics or generative AI engineering are an asset.
Condition of EmploymentAs 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.
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Senior Intelligence Analytics Engineer — Hands-on Technical LeadAs a hands-on technical lead in the Customer Intelligence & Analytics Centre of Excellence (COE), you will own the Customer Office’s gold-layer analytics foundation, validate pipeline design and data quality, automate manual processes, and enable generative AI (GenAI) and agentic AI use cases. You will combine reliable engineering with customer insights, analytics applications, and executive storytelling to build a scalable, AI-ready foundation and support business decisions.
Key responsibilities include:
Own Databricks gold-layer design, including curated and certified datasets, reusable transformation logic, and consistent key performance indicator (KPI) definitions. Partner with Data Engineering to validate pipeline design and end-to-end processing for correctness, scalability, and maintainability.
Analyze customer interaction transcripts, technical and repeat calls, Voice of Customer (VOC) data, customer journeys, and operational KPIs to identify root causes and recommend improvements across customer experience, contact centres, and field operations.
Build Databricks Apps, self-service analytics applications, and executive dashboards with clear user experience and visual storytelling.
Own analytics products from concept through adoption, including requirements gathering, design, development, testing, deployment, and continuous improvement.
Automate report delivery, data preparation, operational analytics workflows, and interactive presentation creation to reduce manual effort and communicate findings, business impacts, and recommendations.
Leverage Copilot, Claude, Genie, and AI technologies to improve productivity and accelerate insights.
Develop GenAI and agentic AI solutions, including intelligent agents, conversational analytics, and decision-support tools, using trusted, governed datasets and validated pipelines.
Establish automated pipeline and data validation, including source-to-target reconciliation and checks for accuracy, completeness, consistency, and freshness. Maintain monitoring to detect reliability issues, investigate failures, and coordinate corrective action.
Provide hands-on technical leadership through design reviews, engineering standards, documentation, and team guidance to support reliable production solutions.
Required Qualifications
At least 7 years of relevant experience in data, analytics, business intelligence, customer intelligence, or related fields, delivering production analytics solutions.
Experience building one or more of the following: AI agents, retrieval-augmented generation (RAG) solutions, conversational analytics solutions, or agentic workflows.
Experience with Databricks, Databricks SQL, and lakehouse architecture.
Demonstrated experience designing and building production-ready analytics applications or self-service analytics products, including Databricks Apps or comparable solutions.
Demonstrated hands‑on experience designing gold‑layer datasets and validating data pipelines, transformation logic, and source-to-target data accuracy, with automated testing, data quality controls, and reliability monitoring.
Experience automating data and analytics workflows and providing hands‑on technical leadership.
Strong SQL and analytical problem‑solving skills, including experience working with large, complex datasets.
Hands‑on Python experience for automation, pipeline and data validation, and GenAI or agentic AI development.
Strong communication and visual storytelling skills, demonstrated through executive dashboards and PowerPoint presentations.
Hands‑on use of Microsoft Copilot, Claude, Databricks Genie, ChatGPT, or comparable tools, with strong prompt engineering skills for analysis, insight generation, content creation, and business recommendations.
Ability to independently lead analytical projects from problem definition through recommendations and presentation.
Experienced in CI/CD, DevOps and automation practices.
Preferred Qualifications
Experience in telecom, contact centres, customer experience, customer care, workforce management, or customer intelligence, particularly with telecom call centre data is an asset.
Experience scaling adoption and continuous improvement of analytics products and AI solutions across business teams.
Experience analyzing transcripts, unstructured text, VOC, sentiment, or conversational intelligence data, and using customer journey analysis to identify friction and connect customer behaviours to operational and business outcomes.
Experience defining KPI frameworks, semantic data models, metric governance, and reusable business logic to support self‑service analytics.
Advanced implementation experience with vector search, RAG architectures, production agentic workflows, and AI assistants, supported by AI governance, large language model (LLM) evaluation and monitoring, and repeatable prompt refinement.
Databricks certifications in data analytics or generative AI engineering are an asset.
Condition of EmploymentAs 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.
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Vacancy posted 1 hour ago
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